Bibliografías temáticas / Identification of risk factors

Literatura académica sobre el tema "Identification of risk factors"

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Publicado: 6 de julio de 2024

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Artículos de revistas sobre el tema "Identification of risk factors":

Bhuyan, K. C. "Identification of Risk Factors for Diabetes Disability among Bangladeshi Adults". Diabetes and Islet Biology 5, n.º 1 (11 de enero de 2022): 01–07. http://dx.doi.org/10.31579/2641-8975/027.

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The paper was to throw some light on the risk factors for diabetes disability among Bangladeshi adults of 18 years and above residing in both urban and rural areas. In investigating the adults, it was decided to cover 50.1% males and 49.9% females to maintain the national level of sex ratio in the sample. The respondents were interviewed when they were visiting some diagnostic centres in urban and semi-urban areas. The percentage of diabetic respondents included in the sample was 67% and 25.5% of them were suffering for 10 years and above, 6.4% were disable against 4.8% total disable respondents in the sample, and obese adults were 30.2%. Diabetic disable adults in the sample were 4.3%. The most responsible variable for diabetes disability was obesity followed by longer duration of diabetes, sedentary activity, smoking habit, being housewife, being married, etc. These variables were identified on the basis of risk ratio and correlation coefficients of variables and discriminant function scores. Beside these variables, rural people, Muslims, adults of ages 40 – 50 years, illiterate people had more risk of facing the problem of diabetes disability.

Upadhyaya, SuneetKumar, Archana Sharma y ChintanM Raval. "Postpartum psychosis: Risk factors identification". North American Journal of Medical Sciences 6, n.º 6 (2014): 35. http://dx.doi.org/10.4103/1947-2714.134373.

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Tuhrim, Stanley. "Stroke Risk Factors". CNS Spectrums 5, n.º 3 (marzo de 2000): 70–74. http://dx.doi.org/10.1017/s1092852900012980.

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AbstractDespite advances in the treatment of acute cerebral infarction, the most effective method of reducing stroke morbidity and mortality is the identification and modification of stroke risk factors. Modifiable stroke risk factors include hypertension, atrial fibrillation, hypercholesterolemia, cigarette smoking, hyperhomocystinemia, and carotid stenosis. Improved identification of individuals at increased stroke risk due to these factors can reduce individual risk and the cost to society of the consequences of stroke.

Ahuja, Dr Ravindra, Dr Ruchi Thakur y Dr Rajat Ahuja. "Identification of Maternal, Environmental and Hygienic Practices as Risk Factors for Diarrhoea". International Journal of Scientific Research 3, n.º 7 (1 de junio de 2012): 390–92. http://dx.doi.org/10.15373/22778179/july2014/120.

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Khan, M. Owais, Rehman Akhtar y Ihtisham Ul Haq. "Risk Factors Identification from Contractors Perspective". Pakistan Journal of Engineering and Technology 5, n.º 2 (27 de septiembre de 2022): 221–25. http://dx.doi.org/10.51846/vol5iss2pp221-225.

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Numerous studies on the distribution of building dangers have been conducted during the last few decades. Even though the current study gives significant insights into the matter, construction industry members are nonetheless concerned about the risks of contracting. A study product was developed to help contracting parties identify, quantify, and assign each construction risk to address this issue. To supplement the model worksheets, flowcharts were created to determine which party should carry which risk, legal research was conducted, and risk allocation guidelines were produced to generate acceptable contract language to address the identified risks. This article focuses on the most significant risks to the project's timeliness, quality, and budget.

Hignett, Sue. "Manual handling risks in midwifery: identification of risk factors". British Journal of Midwifery 4, n.º 11 (noviembre de 1996): 590–96. http://dx.doi.org/10.12968/bjom.1996.4.11.590.

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Razali, Muhammad Najib, Rohaya Abdul Jalil, Kamalahasan Achu y Hishamuddin Mohd Ali. "Identification of Risk Factors in Business Valuation". Journal of Risk and Financial Management 15, n.º 7 (27 de junio de 2022): 282. http://dx.doi.org/10.3390/jrfm15070282.

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It is widely accepted that risk and uncertainty are integral parts of the property valuation process. Uncertainty in property valuation is derived from the characteristics of property itself. The issue pertaining to risk and uncertainty in property valuations is currently one of the key concerns in global valuation practice to date in addressing the decision of risk and uncertainty in valuation, especially for business purposes or in the current term known as business valuation. The judgment and experience still depend on the expertise of the individual valuers alone. The valuation methods used can cause problems if certain elements in business such as risk are highlighted, especially to determine market value. There is a need for valuers to express assumptions which take into account risk and uncertainties, and then pass on the results of the estimation process to the end user of the valuation report. This research employed Analytical Hierarchical Process (AHP) to identify the level of risk in business valuation for valuers to identify which risk areas will expose them to professional liabilities, which then leads to mitigation of risk to determine value in business valuations. AHP will also be able to identify the level of risk in each of the approaches in business valuation which could help valuers to determine the value and market value in the valuation process. This paper will propose some practical approaches of how to address the risk and uncertainty of the valuation process, especially for the purpose of business valuation.

Allam, Mohamed Farouk, Amparo Serrano del Castillo, Carmen Díaz-Molina y Rafael Fernández-Crehuet Navajas. "Invasive Pulmonary Aspergillosis: Identification of Risk Factors". Scandinavian Journal of Infectious Diseases 34, n.º 11 (enero de 2002): 819–22. http://dx.doi.org/10.1080/0036554021000026954.

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Fontana, M., R. Jackson, G. Eckert, N. Swigonski, J. Chin, A. Ferreira Zandona, M. Ando, G. K. Stookey, S. Downs y D. T. Zero. "Identification of Caries Risk Factors in Toddlers". Journal of Dental Research 90, n.º 2 (20 de diciembre de 2010): 209–14. http://dx.doi.org/10.1177/0022034510385458.

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Yang, Zhenhua, Ying Kong, Frank Wilson, Betsy Foxman, Annadell H. Fowler, Carl F. Marrs, M. Donald Cave y Joseph H. Bates. "Identification of Risk Factors for Extrapulmonary Tuberculosis". Clinical Infectious Diseases 38, n.º 2 (15 de enero de 2004): 199–205. http://dx.doi.org/10.1086/380644.

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Tesis sobre el tema "Identification of risk factors":

Cummins, Robert W. "Identification of commercial items risk factors". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Mar%5FCummins.pdf.

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Thesis (M.S. in Software Engineering)--Naval Postgraduate School, March 2003.
Thesis advisor(s): Norman Schneidewind, Richard Riehle. Includes bibliographical references (p. 162-168). Also available online.

Giedraitytė, Lina. "Identification of risk factors in cold work /". Luleå, 2002. http://epubl.luth.se/1402-1757/2002/22.

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Giedraitytė, Lina. "Identification and validation of risk factors in cold work /". Luleå, 2005. http://epubl.luth.se/1402-1544/2005/24.

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Zeng, Yanni. "The identification of risk factors for major depressive disorder". Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28702.

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For complex traits, population genetic studies ask: to what extent do genetic variation and environmental variation influence, determine and predict phenotypic variation? More specifically, researchers ask two questions. First, how much of the phenotypic variation is genetic in origin? Second, if the genetic component of a trait has been ascertained, then by what mechanisms do the causal variants contribute to the genetic variation that impacts on the phenotype? Previous studies have indicated a polygenic structure for many complex traits, which means that the genetic variation in those traits is the result of the cumulative effect from hundreds or even thousands of genetic variants. To further decipher the polygenic genetic architecture of a complex trait, genetic studies aim to identify the number, the location in the genome, and the distribution of the effect sizes of causal variants, as well as their individual and interacting effects. Linkage analysis and genome-wide association studies (GWAS), either based on single variants or sets of variants categorized by functional annotations, can be applied to map the potentially causal variants in the genome. The identification of disease-associated loci, however, is only the starting point in identifying causal variants. Causal variants are usually difficult to distinguish from the large number of variants in linkage disequilibrium (LD) within the associated loci, and may be in incomplete LD with genotyped variants. Computational prediction integrated with multi-level ‘Omic’ data will help the prioritization of candidate causal variants, which then become important targets for experimental validation (Chapter 1). Major depressive disorder (MDD) is a complex trait, contributes the second most important burden to global disease. Both genetic and environmental components have been suggested for this disorder in previous studies, although a clear partitioning of the contribution of each component and the identification of major contributing components is yet to be achieved. In efforts to map causal genetic variants, genome-wide association studies of MDD have identified few significant associations so far. The polygenic architecture combined with the widespread clinical and genetic heterogeneity of MDD between populations may impede the identification of causal variants (Chapter 2). In this thesis, I will present three studies; the first study estimated the proportions of the phenotypic variation that are genetic or familial environmental in origin in two depression definitions(chapter 3), followed by two studies where distinct (non- GWAS) methods were used to identify candidate causal genetic variants for MDD (chapter 4,5). In detail, in chapter 3, a variance component analysis was applied to GS:SFHS (Generation Scotland: Scottish Family Health Study) to investigate the relative genetic and environmental contributions to diagnosed major depressive disorder (MDD) and self-declared depression (SDD). Models for MDD and SDD that simultaneously included genetic and environmental effects suggested that narrow-sense heritability could be inflated by the environments shared by nuclear family members. The most parsimonious models selected for both MDD and SDD included SNP and pedigree-associated genetic effects and the effect of the common environment of couples. In chapter 4, I integrated pathway analysis and multi-level regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS studies (GS:SFHS and PGC1-MDD). The NETRIN1 signalling pathway showed the most consistent association with MDD across the two samples. Polygenic risk scores (PRSs) from this pathway showed predictive accuracy better than whole-genome PRSs when using AUC statistics, logistic regression and the linear mixed model. In chapter 5, genome-wide Haplotype-block-based regional heritability mapping (HRHM) was applied to identify haplotype blocks significantly contributing to MDD. A haplotype block across a 24kb region within the TOX2 gene reached genotype-wide significance in GS:SFHS. Single-SNP and haplotype based association tests were used to localize the association signal within the region identified by HRHM, and demonstrated that five out of nine genotyped SNPs and two haplotypes were significantly associated with MDD. The results were replicated in the UK-Ireland group in PGC2-MDD. The brain expression of TOX2 and brain-specific LncRNA RP1-269M15.3 were also significantly regulated by MDD-associated SNPs within the identified haplotype block. The three studies highlight the value of the application of multiple population genetics and bioinformatics methods to multiple family-based and population-based cohorts in identification of risk factors for MDD.

Dickson, Laurie Marie. "Youth gambling problems : the identification of risk and protective factors". Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85150.

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The present study examined the relationship between several risk and protective variables associated with problem gambling, substance abuse, and other multiple risk-taking activities by adolescents. With the goal of identifying protective factors that prevent youth from escalating from social gambling to serious problem gambling, this research examined the relationship between family cohesion, school connectedness, coping and adaptive behaviours, mentor relationships, achievement motivation, involvement in conventional organizations, and the development of three health-compromising outcomes---youth problem gambling, substance abuse, and involvement in multiple risk-taking behaviours (e.g., smoking, unsafe sexual activity, and reckless driving). The sample consisted of 2,179 students, ages 11 to 19, in the Province of Ontario. Family and school connectedness were associated with decreased involvement in excessive gambling, substance use, and multiple risk-taking activities. Furthermore, an examination of the effect of potential protective factors on a set of risk factors predictive of adolescent problem gambling suggested that family cohesion plays a role in the prediction of probable pathological gamblers and those at risk for developing a gambling problem. These findings were interpreted with respect to their implications for the development and implementation of prevention programs.

Bhambra, Upinder Kaur. "Heterocyclic amines and human colon cancer : identification of risk factors". Thesis, Imperial College London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.406359.

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Bassement, Jennifer. "Identification of fall-risk factors degradation using quality of balance measurements". Thesis, Troyes, 2014. http://www.theses.fr/2014TROY0035/document.

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Les chutes touchent un tiers des personnes âgées de 65 ans et plus et conduit à une perte de mobilité. La détection des risques facteurs de chutes est essentielle pour une intervention précoce.Six facteurs intrinsèques de chute : vision, système vestibulaire, amplitude articulaire, force musculaire, proprioception articulaire et plantaire ont été évalué par des tests cliniques avant et après une dégradation temporaire. L’équilibre a été évalué sur une plateforme de force pour le calcul de 198 paramètres.Les paramètres ont été utilisés comme variables pour la construction de modèle de réseaux de neurones et de régression logistique avec pour objectif de diagnostiquer les détériorations des facteurs testés. Les paramètres pertinents ont été sélectionnés pour être inclus aux modèles. Des modèles comprenant entre 3 et 10 conditions ont été développé, néanmoins seuls les modèles de 5 conditions et moins se sont révélés efficaces. La précision a réussi à atteindre 92% pour le modèle incluant l’amplitude de la cheville, la fatigue et la vision des contrastes.Les mesures de qualité d’équilibre ont permis de détecter des détériorations des facteurs intrinsèques testés. Cependant, ces modèles ne sont efficaces qu’avec peu de conditions. Pour construire un modèle performant avec plusieurs conditions il est nécessaire d’inclure plus de participants lors de la construction du modèle. Un outil de la sorte est intéressant pour la mise en place de programmes de prévention et de rééducation
Falls concern a third of the people aged over 65y and lead to the loss of functional ability. The detection of risks factors of falls is essential for early intervention. Six intrinsic risk factors of fall: vision, vestibular system, joint range of motion, leg muscle strength, joint proprioception and foot cutaneous proprioception were assessed with clinical tests before and after temporarily degradation. Standing balance was recorded on a force plate.From the force plate, 198 parameters of the centre of pressure displacement were computed. The parameters were used as variables to build neural network and logistic regression model for discriminating conditions. Feature selection analysis was performed to reduce the number of variables.Several models were built including 3 to 10 conditions. Models with 5 or less conditions appeared acceptable but better performance was found with models including 3 conditions. The best accuracy was 92% for a model including ankle range of motion, fatigue and vision contrast conditions. Qualities of balance parameters were able to diagnose impairments. However, the efficient models included only a few conditions. Models with more conditions could be built but would require a larger number of cases to reach high accuracy. The study showed that a neural network or a logistic model could be used for the diagnosis of balance impairments. Such a tool could seriously improve the prevention and rehabilitation practice

Kopplin, Laura J. "The Identification of Genetic Risk Factors for Age-Related Macular Degeneration". Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1251752708.

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Hawkins, Richard D. "Injuries in professional football : identification of aetiological factors". Thesis, Loughborough University, 1998. https://dspace.lboro.ac.uk/2134/7520.

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UK health and safety legislation aims to protect employees from injury at work; professional footballers as employees are therefore covered by this legislation. A risk assessment approach to health and safety issues, as required by the Management of Health and Safety at Work Regulations 1992, has been undertaken to establish the epidemiological and aetiological factors related to injuries in professional football and to identify management and training procedures to reduce the incidence and severity of injuries. Issues of injury frequency and causation during the period 1994 to 1997 were addressed through two routes. First, during the 1994 World Cup Finals, 1996 European Championships, and 1994 to 1997 English league seasons via match analysis. Second, player injuries at four professional football league clubs were recorded by the club physiotherapist. These results provided complementary evidence showing an overall injury rate of 8.5/1000 playing hours, injury rates during training and matches being 3.5/1000 and 27.7/1000 playing hours, respectively. Two thirds of the injuries occurred during competitive match play, the remainder during training, the highest incidences of match and training injuries taking place during the first month of the playing season (P

Mokone, Gaonyadiwe George. "Risk factors for Achilles tendon injuries : an emphasis on the identification of specific genetic factors". Doctoral thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/3270.

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Includes bibliographical references.
This main purpose of this thesis was therefore to investigate whether any specific genes on the tip of the long arm of chromosome 9 were associated with Achilles tendon injuries, using a case-control study design. The specific objectives were: (i) to identify all genes located in the 9q32-q34.3 locus in close proximity to the ABO gene, that could be involved in tendon injuries (Chapter 2) and (ii) to investigate the possible association of the identified candidate genes (COL5A1 and TNC with both Achilles tendon rupture and chronic Achilles tendinopathy (Chapter 3 and 4) and (iii) finally to investigate the possible interaction of these two genes with tendon function, namely the muscle-tendon unit flexibility (chapter 5) and structure, namely the morphological changes of the Achilles tendon (Chapter 6).

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Libros sobre el tema "Identification of risk factors":

R, Johnston Janet, ed. Early identification of risk factors for parental abduction. Washington, D.C: U.S. Dept. of Justice, Office of Justice Programs, Office of Juvenile Justice and Delinquency Prevention, 2001.

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1947-, Vainio H. y International Agency for Research on Cancer., eds. Mechanisms of carcinogenesis in risk identification. Lyon, France: International Agency for Research on Cancer, 1992.

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1947-, Vainio H. y International Agency for Research on Cancer., eds. Mechanisms of carcinogenesis in risk identification. Lyon: International Agency for Research on Cancer, 1992.

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Thow, Anne Marie. Diabetes in culturally and linguistically diverse Australians: Identification of communities at high risk. Canberra: Australian Institute of Health and Welfare, 2005.

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Wu, James T. Early risk assessment of cancer and atherosclerosis: Identification of common risk markers, and preventive nutrition. Washington, DC: AACC Press, 2004.

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Pasqualina, Santaguida, United States. Agency for Healthcare Research and Quality. y McMaster University. Evidence-based Practice Center., eds. Diagnosis, prognosis, and treatment of impaired glucose tolerance and impaired fasting glucose. [Rockville, Md: Agency for Healthcare Research and Quality, 2005.

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International Conference on Hazard Identification and Risk Analysis, Human Factors, and Human Reliability In Process Safety (1992 Orlando, Fla.). International Conference on Hazard Identification and Risk Analysis, Human Factors, and Human Reliability In Process Safety: January 15-17, 1992, Marriott Hotel (airport) Orlando, Florida. New York: The Center, 1992.

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Maciejko, James J. Atherosclerosis Risk Factors. Washington, DC: AACC Press, 2004.

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Swales, J. D. Cardiovascular risk factors. London: Gower Medical Pub., 1993.

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S, Honig Alice, ed. Risk factors in infancy. New York: Gordon and Breach Science Publishers, 1986.

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Capítulos de libros sobre el tema "Identification of risk factors":

Hong, Keun-Sik. "Identification of Vascular Risk Factors". En Stroke Revisited: Diagnosis and Treatment of Ischemic Stroke, 247–53. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-1424-6_23.

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Ardehali, Ali, Ishwari Casikar y George Condous. "Identification of Risk Factors of Ectopic Pregnancy". En Ectopic Pregnancy, 1–10. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11140-7_1.

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Di Renzo, Gian Carlo, Elena Pacella, Laura Di Fabrizio y Irene Giardina. "Preterm Birth: Risk Factors, Identification and Management". En Management and Therapy of Late Pregnancy Complications, 81–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48732-8_6.

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Wu, James T. "Identification of Risk Factors for Early Neoplasm". En Cancer Diagnostics, 53–64. Totowa, NJ: Humana Press, 2004. http://dx.doi.org/10.1007/978-1-59259-791-8_5.

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Sameroff, Arnold J. "Environmental Factors in the Early Screening of Children at Risk". En Early Identification of Children at Risk, 21–44. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-0536-9_2.

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Jiang, Guo-ping y Ming-chi Lin. "Identification of Critical Risk Factors in Software Project Risk Management". En The 19th International Conference on Industrial Engineering and Engineering Management, 1065–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38433-2_112.

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Schiffner, Julia, Erhard Godehardt, Stefanie Hillebrand, Alexander Albert, Artur Lichtenberg y Claus Weihs. "Identification of Risk Factors in Coronary Bypass Surgery". En Algorithms from and for Nature and Life, 287–95. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00035-0_29.

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Dovjak, Mateja y Andreja Kukec. "Identification of Health Risk Factors and Their Parameters". En Creating Healthy and Sustainable Buildings, 83–120. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19412-3_3.

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Lau, Timothy, Elizabeth Kozyra y Catherine Cheng. "Delirium: Risk Factors, Contributors, Identification, Work-Up, and Treatment". En Inpatient Geriatric Psychiatry, 219–35. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10401-6_12.

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Yu, Chun-hua, Li-ping Tian y Zeng-chang Zhao. "Identification of Risk Factors for Casualty in Building Fires". En The 19th International Conference on Industrial Engineering and Engineering Management, 567–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37270-4_54.

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Actas de conferencias sobre el tema "Identification of risk factors":

Palihakkara, A. D. y B. A. K. S. Perera. "IDENTIFICATION OF SIGNIFICANT RISK FACTORS OF GUARANTEED MAXIMUM PRICE (GMP) CONTRACTS". En The 9th World Construction Symposium 2021. The Ceylon Institute of Builders - Sri Lanka, 2021. http://dx.doi.org/10.31705/wcs.2021.30.

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The construction industry is a risk-prone industry where projects are implemented in a dynamic environment with frequent exposure to various uncertainties. A construction contract is a document that allocates the risks associated with a construction project among the project stakeholders. Guaranteed Maximum Price (GMP) contracts have become popular as a project delivery method because they provide the client with a high degree of cost certainty through a fixed price cap that the contractor cannot exceed. However, most of the GMP projects are risky. Thus, the significant risk factors of GMP projects have to be identified to ensure their successful completion. This study, therefore, aimed to identify and rank the most significant risk factors present in GMP contracts. The study adopted a quantitative approach, which included a Delphi survey conducted in two rounds and a statistical analysis of the survey data. The most significant risk factors associated with GMP contracts were ranked according to their impact on the projects and their probability of occurrence (severity). Poorly defined scope of work and design changes were found to be the most significant risk factors associated with GMP contracts. The other significant risk factors of the projects are related to the scope of work, design, documentation, unfamiliarity with the GMP concept, agreed GMP value, and financial failures of the client and contractor.

Alban, Lis, G. Pacheco y J. V. Petersen. "Risk-based Surveillance of Antimicrobial Residues – Identification of Potential Risk Factors". En 10th International Conference on the Epidemiology and Control of Biological, Chemical and Physical Hazards in Pigs and Pork. Iowa State University, Digital Press, 2013. http://dx.doi.org/10.31274/safepork-180809-907.

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Paul, Topon K., Ken Ueno, Koichiro Iwata, Toshio Hayashi y Nobuyoshi Honda. "Risk prediction and risk factors identification from imbalanced data with RPMBGA+". En the 2008 GECCO conference companion. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1388969.1389046.

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Dicks, Evan P. y Keith R. Molenaar. "Identification of Critical Transportation Risk Factors Using DEMATEL". En Construction Research Congress 2024. Reston, VA: American Society of Civil Engineers, 2024. http://dx.doi.org/10.1061/9780784485286.008.

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Tang, Tianpei, Senlai Zhu y Yang Cao. "Safety Risk Factors Identification and Safety Risk Classification Assessment for Rural Roadsides". En 19th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2019. http://dx.doi.org/10.1061/9780784482292.336.

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Wang, Xin, Liling Yu y Lingyun Miao. "Research on Identification of Risk Factors in Civil Airports". En 2019 5th International Conference on Transportation Information and Safety (ICTIS). IEEE, 2019. http://dx.doi.org/10.1109/ictis.2019.8883675.

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Nomaguchi, Yutaka, Chunzhi Dong, Hirotaka Nakashima y Kikuo Fujita. "Risk Identification Method for Engineering Design Project Based on Risk Chain Mechanism Model". En ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47155.

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An engineering design project includes various types of uncertainties. They cause risk that a project goal cannot be accomplished within lead time. A design project manager should identify potential risk factors and causal relations among them in a project. Although it is worthwhile to spend much time on a workshop for project members to understand unnoticed risks, it is often a hard job to identify risk factors and causal relations in a mutually exclusive and collectively exhaustive way. This paper proposes a risk identification method based on a fundamental model of a risk chain mechanism in an engineering design project in order to support a project manager and project members to systematically identify potential risk factors and causal relations among them. A proposed method provides categories of typical risk factors in an engineering design project. A typical chain mechanism among those categories is also defined. Those elements in a fundamental model can facilitate a project manager and project members to find unnoticed factors in a project. A case study of a risk workshop for a student formula car design project is demonstrated to show that the proposed method facilitates project members to understand potential risk factors and to build a comprehensive risk chain model.

Boytcheva, Svetla, Ivelina Nikolova, Galia Angelova y Zhivko Angelov. "Identification of Risk Factors in Clinical Texts through Association Rules". En RANLP 2017 - Biomedical NLP Workshop. Incoma Ltd. Shoumen, Bulgaria, 2017. http://dx.doi.org/10.26615/978-954-452-044-1_009.

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Peng, Shirui, Guofeng Su, Jianguo Chen y Zhiru Wang. "Method Construction for Risk Factors Identification of Public Hospital Operation". En 2016 International Conference on Industrial Engineering, Management Science and Application (ICIMSA). IEEE, 2016. http://dx.doi.org/10.1109/icimsa.2016.7504017.

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Ueno, A., M. Hirata, Y. Yamamura, K. Fujita, N. Shibutou y M. Yamamura. "AB0646 Identification of risk factors for recurrence in polymyalgia rheumatica". En Annual European Congress of Rheumatology, EULAR 2018, Amsterdam, 13–16 June 2018. BMJ Publishing Group Ltd and European League Against Rheumatism, 2018. http://dx.doi.org/10.1136/annrheumdis-2018-eular.7128.

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Informes sobre el tema "Identification of risk factors":

Shea, M. T. y Norman J. Hebert. Identification of Risk Factors for Chronic Posttraumatic Stress Disorder (PTSD). Fort Belvoir, VA: Defense Technical Information Center, julio de 2007. http://dx.doi.org/10.21236/ada484221.

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Shea, M. T. Identification of Risk Factors for Chronic Posttraumatic Stress Disorder (PTSD). Fort Belvoir, VA: Defense Technical Information Center, junio de 2009. http://dx.doi.org/10.21236/ada524923.

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Yang, Kelu, Lin Chen, Yingying Kang, Lina Xing, Hailing Li, Peng Cheng y Zonghui Song. Identification of risk factors of developing pressure injuries among immobile patient, and a risk prediction model establishment: Protocol for a systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, octubre de 2020. http://dx.doi.org/10.37766/inplasy2020.10.0097.

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Reyero y Aranda, María Rosa. Identification of Institutional Factors in Bank Operations: Flexibility v. Early Detection: Case Studies in the Citizen Security and Transparency Sub-Sectors. Inter-American Development Bank, enero de 2011. http://dx.doi.org/10.18235/0006789.

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The study seeks to survey the prevalence of institutional factors posing risks or vulnerabilities to selected Bank operations and the time at, and mechanisms through which these are addressed. As a first study, it focuses on two sub-sectors of the Reform and Modernization of the State sector: Citizen Security and Transparency and Anti-Corruption. The study unfolds in three segments: 1) to identify institutional factors and their impact on sub-sector operations through document review, interviews and other Bank information sources; 2) pointing to existing Bank approaches of addressing institutional factors and suggesting new considerations for their dealing in light of the analysis of survey results, as might be the false dichotomy of early identification v. flexibility; and 3) to cross-check the study's findings on the presence of institutional factors with those yielded by the Matrix of Institutional Factors (MAFI) developed for ICF/ICS, as to assess its effectiveness in factor identification. The main conclusion of the study is that both flexibility and implementation are important elements in project design, at least in the sub-sectors studied.

Daudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe y Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, diciembre de 2021. http://dx.doi.org/10.53328/uxuo4751.

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The report provides a review of how risk is conceived of, modelled, and mapped in studies of infectious water, sanitation, and hygiene (WASH) related diseases. It focuses on spatial epidemiology of cholera, malaria and dengue to offer recommendations for the field of WASH-related disease risk mapping. The report notes a lack of consensus on the definition of disease risk in the literature, which limits the interpretability of the resulting analyses and could affect the quality of the design and direction of public health interventions. In addition, existing risk frameworks that consider disease incidence separately from community vulnerability have conceptual overlap in their components and conflate the probability and severity of disease risk into a single component. The report identifies four methods used to develop risk maps, i) observational, ii) index-based, iii) associative modelling and iv) mechanistic modelling. Observational methods are limited by a lack of historical data sets and their assumption that historical outcomes are representative of current and future risks. The more general index-based methods offer a highly flexible approach based on observed and modelled risks and can be used for partially qualitative or difficult-to-measure indicators, such as socioeconomic vulnerability. For multidimensional risk measures, indices representing different dimensions can be aggregated to form a composite index or be considered jointly without aggregation. The latter approach can distinguish between different types of disease risk such as outbreaks of high frequency/low intensity and low frequency/high intensity. Associative models, including machine learning and artificial intelligence (AI), are commonly used to measure current risk, future risk (short-term for early warning systems) or risk in areas with low data availability, but concerns about bias, privacy, trust, and accountability in algorithms can limit their application. In addition, they typically do not account for gender and demographic variables that allow risk analyses for different vulnerable groups. As an alternative, mechanistic models can be used for similar purposes as well as to create spatial measures of disease transmission efficiency or to model risk outcomes from hypothetical scenarios. Mechanistic models, however, are limited by their inability to capture locally specific transmission dynamics. The report recommends that future WASH-related disease risk mapping research: - Conceptualise risk as a function of the probability and severity of a disease risk event. Probability and severity can be disaggregated into sub-components. For outbreak-prone diseases, probability can be represented by a likelihood component while severity can be disaggregated into transmission and sensitivity sub-components, where sensitivity represents factors affecting health and socioeconomic outcomes of infection. -Employ jointly considered unaggregated indices to map multidimensional risk. Individual indices representing multiple dimensions of risk should be developed using a range of methods to take advantage of their relative strengths. -Develop and apply collaborative approaches with public health officials, development organizations and relevant stakeholders to identify appropriate interventions and priority levels for different types of risk, while ensuring the needs and values of users are met in an ethical and socially responsible manner. -Enhance identification of vulnerable populations by further disaggregating risk estimates and accounting for demographic and behavioural variables and using novel data sources such as big data and citizen science. This review is the first to focus solely on WASH-related disease risk mapping and modelling. The recommendations can be used as a guide for developing spatial epidemiology models in tandem with public health officials and to help detect and develop tailored responses to WASH-related disease outbreaks that meet the needs of vulnerable populations. The report’s main target audience is modellers, public health authorities and partners responsible for co-designing and implementing multi-sectoral health interventions, with a particular emphasis on facilitating the integration of health and WASH services delivery contributing to Sustainable Development Goals (SDG) 3 (good health and well-being) and 6 (clean water and sanitation).

Shpigel, Nahum Y., Ynte Schukken y Ilan Rosenshine. Identification of genes involved in virulence of Escherichia coli mastitis by signature tagged mutagenesis. United States Department of Agriculture, enero de 2014. http://dx.doi.org/10.32747/2014.7699853.bard.

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Mastitis, an inflammatory response of the mammary tissue to invading pathogenic bacteria, is the largest health problem in the dairy industry and is responsible for multibillion dollar economic losses. E. coli are a leading cause of acute mastitis in dairy animals worldwide and certainly in Israel and North America. The species E. coli comprises a highly heterogeneous group of pathogens, some of which are commensal residents of the gut, infecting the mammary gland after contamination of the teat skin from the environment. As compared to other gut microflora, mammary pathogenic E. coli (MPEC) may have undergone evolutionary adaptations that improve their fitness for colonization of the unique and varied environmental niches found within the mammary gland. These niches include competing microbes already present or accompanying the new colonizer, soluble and cellular antimicrobials in milk, and the innate immune response elicited by mammary cells and recruited immune cells. However, to date, no specific virulence factors have been identified in E. coli isolates associated with mastitis. The original overall research objective of this application was to develop a genome-wide, transposon-tagged mutant collection of MPEC strain P4 and to use this technology to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. In the course of the project we decided to take an alternative genome-wide approach and to use whole genomes bioinformatics analysis. Using genome sequencing and analysis of six MPEC strains, our studies have shown that type VI secretion system (T6SS) gene clusters were present in all these strains. Furthermore, using unbiased screening of MPEC strains for reduced colonization, fitness and virulence in the murine mastitis model, we have identified in MPEC P4-NR a new pathogenicity island (PAI-1) encoding the core components of T6SS and its hallmark effectors Hcp, VgrG and Rhs. Next, we have shown that specific deletions of T6SS genes reduced colonization, fitness and virulence in lactating mouse mammary glands. Our long-term goal is to understand the molecular mechanisms of host-pathogen interactions in the mammary gland and to relate these mechanisms to disease processes and pathogenesis. We have been able to achieve our research objectives to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. The project elucidated a new basic concept in host pathogen interaction of MPEC, which for the best of our knowledge was never described or investigated before. This research will help us to shed new light on principles behind the infection strategy of MPEC. The new targets now enable prevalence and epidemiology studies of T6SS in field strains of MPEC which might unveil new geographic, management and ecological risk factors. These will contribute to development of new approaches to treat and prevent mastitis by MPEC and perhaps other mammary pathogens. The use of antibiotics in farm animals and specifically to treat mastitis is gradually precluded and thus new treatment and prevention strategies are needed. Effective mastitis vaccines are currently not available, structural components and effectors of T6SS might be new targets for the development of novel vaccines and therapeutics.

Carr, Marvin J., Suresh L. Konda, Ira Monarch, F. C. Ulrich y Clay F. Walker. Taxonomy-Based Risk Identification. Fort Belvoir, VA: Defense Technical Information Center, junio de 1993. http://dx.doi.org/10.21236/ada266992.

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Jauny, Ray y John Parsons. Delirium Assessment and Management: A qualitative study on aged-care nurses’ experiences. Unitec ePress, noviembre de 2017. http://dx.doi.org/10.34074/ocds.72017.

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Aged residential care (ARC) residents with morbid health conditions frequently experience delirium. This condition is associated with diminished quality of life, preventable morbidity and untimely death. It is challenging and costly to manage delirium because of the complex interplay of physical and psychiatric symptoms associated with this condition in both primary and secondary services. With awareness of risk factors and knowledge about delirium, ARC nurses can play a vital role in early identification, assessment and treatment, but most importantly in preventing delirium in aged-care residents as well as improving health outcomes. Focus groups were carried out with ARC nurses to ascertain their opinions on how they assess and manage delirium in ARC facilities in South Auckland, New Zealand. Findings identified that there were strengths and weaknesses, as well as gaps in assessment and management of delirium. Nurses would benefit from delirium education, appropriate tools and adequate resources to help them manage delirium. Issues with diagnosing delirium, anxiety about challenging behaviours, family dynamics, lack of training and absence of IV treatment were noticeable features in this study.

Almås, Ingvild, Orazio Attanasio, Jyotsna Jalan, Francisco Oteiza y Marcella Vigneri. Using data differently and using different data. Centre for Excellence and Development Impact and Learning (CEDIL), 2018. http://dx.doi.org/10.51744/cip8.

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The lack of adequate measures to capture relevant factors, and the prevalence of measurement error in existing ones, often constitute the main impediment to robust policy evaluation. Random assignment of a given treatment, when feasible, may allow for the identification of causal effects, given that the necessary measurements are available. Measurement challenges include: (a) adequately measuring outcomes of interest; (b) measuring factors that relate to the mechanisms of estimated impacts; and (c) conducting a robust evaluation in areas where the RCT methodology is not feasible. In this paper, we discuss three categories of related approaches to innovation in the use of data and measurements relevant for evaluation: the creation of new measures, the use of multiple measures, and the use of machine learning algorithms. We motivate the relevance of each of the categories by providing a series of detailed examples of cases where each approach has proved useful in impact evaluations. We discuss the challenges and risks involved in each strategy and conclude with an outline of promising directions for future work.