Academic literature on the topic 'Biais cognitifs – Diagnostic'
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Journal articles on the topic "Biais cognitifs – Diagnostic"
Field, Morton H. "Cognitive bias and diagnostic error (November 2015)." Cleveland Clinic Journal of Medicine 83, no. 6 (June 2016): 407–8. http://dx.doi.org/10.3949/ccjm.83c.06003.
Full textAoki, Yosuke. "2. Introducing Representative Cognitive Bias (in Diagnostic Reasoning)." Nihon Naika Gakkai Zasshi 108, Suppl (February 28, 2019): 139b—140a. http://dx.doi.org/10.2169/naika.108.139b.
Full textAoki, Yosuke. "2. Introducing Representative Cognitive Bias (in Diagnostic Reasoning)." Nihon Naika Gakkai Zasshi 108, no. 9 (September 10, 2019): 1842–46. http://dx.doi.org/10.2169/naika.108.1842.
Full textNichols, Emma, Yizhou Chen, Adina Zeki Al Hazzouri, Alden Gross, Niranjani Nagarajan, Jinkook Lee, and Joshua Ehrlich. "VISION IMPAIRMENT AND COGNITION IN INDIA: ASSOCIATIONS AFTER ADJUSTMENT FOR POTENTIAL BIAS." Innovation in Aging 7, Supplement_1 (December 1, 2023): 1156–57. http://dx.doi.org/10.1093/geroni/igad104.3711.
Full textMull, Nikhil, James B. Reilly, and Jennifer S. Myers. "In reply: Cognitive bias and diagnostic error (November 2015)." Cleveland Clinic Journal of Medicine 83, no. 6 (June 2016): 408. http://dx.doi.org/10.3949/ccjm.83c.06004.
Full textWatari, Takashi, Yasuharu Tokuda, Yu Amano, Kazumichi Onigata, and Hideyuki Kanda. "Cognitive Bias and Diagnostic Errors among Physicians in Japan: A Self-Reflection Survey." International Journal of Environmental Research and Public Health 19, no. 8 (April 12, 2022): 4645. http://dx.doi.org/10.3390/ijerph19084645.
Full textNosker, Jennifer L., Stephen L. Aita, Nicholas C. Borgogna, Tina Jimenez, Keenan A. Walker, Tasha Rhoads, Janelle M. Eloi, Zachary J. Resch, and Victor A. Del Bene. "35 The Effect of Diagnostic Method on Racial Disparities in Mild Cognitive Impairment and Dementia Diagnosis Using the NACC Database." Journal of the International Neuropsychological Society 29, s1 (November 2023): 909–10. http://dx.doi.org/10.1017/s1355617723011177.
Full textBurke, Shanna L., Miriam J. Rodriguez, Warren Barker, Maria T. Greig-Custo, Monica Rosselli, David A. Loewenstein, and Ranjan Duara. "Relationship between Cognitive Performance and Measures of Neurodegeneration among Hispanic and White Non-Hispanic Individuals with Normal Cognition, Mild Cognitive Impairment, and Dementia." Journal of the International Neuropsychological Society 24, no. 2 (September 18, 2017): 176–87. http://dx.doi.org/10.1017/s1355617717000820.
Full textLoving, Vilert A., Elizabeth M. Valencia, Bhavika Patel, and Brian S. Johnston. "The Role of Cognitive Bias in Breast Radiology Diagnostic and Judgment Errors." Journal of Breast Imaging 2, no. 4 (April 29, 2020): 382–89. http://dx.doi.org/10.1093/jbi/wbaa023.
Full textOlson, Robert, Maureen Parkinson, and Michael McKenzie. "Selection Bias Introduced by Neuropsychological Assessments." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 37, no. 2 (March 2010): 264–68. http://dx.doi.org/10.1017/s0317167100010039.
Full textDissertations / Theses on the topic "Biais cognitifs – Diagnostic"
Fouillard, Valentin. "La logique des incohérences : un modèle formel pour l'analyse de l'erreur humaine." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG082.
Full textIn this thesis, we are interested in the use of formal methods to guide the diagnosis of human errors in accident situations. The application of formal methods in such a context raises several difficulties. The first one is to be able to explain with the help of mathematical logic situations that are incoherent and therefore in contradiction with this logic. The second is to be able to compare the different diagnoses. Indeed, an incorrect decision is never the work of a hazard but is based on the beliefs, desires and intentions of the operator. Thus, not all errors are equal and it is necessary to formalize and define what makes a good diagnosis. The first part of the thesis presents a state of the art of human and social sciences (HSS) work on human error. We show that it is necessary to distinguish two aspects: the determination of the causes of erroneous decision making and the understanding of these causes through the search for cognitive biases. We then present the main computer models for modeling reasoning and studying human error. We show that consistency-based diagnosis and the belief revision operator AGM is a good way to explain human errors. The second part of the thesis deals with the modeling of an accident situation and the diagnosis of human errors in this situation. We have based our work on a belief logic inspired by the BDI logic for the modeling of accident situations. We have developed an iterative diagnosis algorithm based on a minimal belief revision operator respecting the AGM axiomatic. This iterative diagnosis algorithm has the advantage of facilitating the distinction of errors of different nature. Moreover, it is correct and complete compared to a minimal diagnosis algorithm. The third contribution of the thesis lies in our work to formally define the plausibility of a diagnosis. We based our work on the literature of human sciences and more precisely on cognitive biases. For this purpose, we have developed a first formal taxonomy of biases that allows us to define common logical characteristics between biases. From this taxonomy, we were able to define eight cognitive biases related to the biases present in the literature. We then considered that the more a diagnosis can be explained by the biases, the more plausible the diagnosis is. We then studied the validity of this computer model on two cases of civil aviation accidents. We show that we find the explanations proposed by the Bureau d'Enquêtes et d'Analyses as well as explanations not considered by the investigators. Finally, we propose several perspectives to improve our approach. In particular, we intend to take into account emotions and social interactions in the modeling of the accident situation in order to increase the variety of possible diagnoses. Finally, we wish to extend the evaluation of the diagnoses by a meta-evaluation of the cognitive biases as well as by taking into account the intention of action
Thomas, Richard. "A comparison of methodologies in a diagnostic overshadowing study : clinical impressions of short case presentations." Thesis, University of Southampton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288441.
Full textMoro, Bruna Lorena Pereira. "A experiência de cárie da criança influencia o desempenho dos examinadores na detecção de lesões proximais de cárie em dentes decíduos?" Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/23/23132/tde-07062017-152253/.
Full textDespite many studies have already been conducted to investigate the accuracy of caries detection methods, few investigations have evaluated the influence of some factors on the examiners\' performance, such as child\'s caries experience. Thus, this study aimed to evaluate if the child\'s caries experience exerts some influence on the performance of visual and radiographic methods for the detection of approximal caries lesions in primary molars. Eighty children aged from 3 to 6 years were selected and classified according to the past caries experience considering cavitated lesions. Two calibrated examiners evaluated 526 approximal surfaces for the presence of caries lesions using visual inspection and radiographic methods. As reference standard, two other examiners checked the surfaces by direct visual inspection after the temporary separation with orthodontic rubbers. Sensitivity, specificity, and accuracy obtained with visual inspection and radiographic method, alone or associated, were calculated and compared considering non-cavitated and cavitated lesions thresholds. Poisson multilevel regression analyses were conducted to evaluate the influence of the caries experience on the performance of diagnostic strategies. Radiographic examination and visual inspection performed associated did not improve the accuracy in detecting approximal caries lesions in both thresholds. However, an influence of child\'s caries experience was observe only on the visual inspection. The detection of non-cavitated caries lesions in children with higher caries experience was overestimated, probably due to confirmation bias. On the other hand, considering cavitated caries lesions, the performance of visual inspection was underestimated, indicating the occurrence of representativeness bias. Nevertheless, the radiographic method did not suffer influence of any type of cognitive bias, and the performance of this method, alone or simultaneously associated with visual inspection, was better in children with higher caries experience. In conclusion, the child\'s caries experience exerts influence on visual inspection in detecting approximal caries lesions in primary teeth.
Books on the topic "Biais cognitifs – Diagnostic"
Ryle, Cym Anthony. Risk and Reason in Clinical Diagnosis. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780190944001.001.0001.
Full textGerken, Mikkel. Diagnosing Salient Alternative Effects. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198803454.003.0011.
Full textvan Schalkwyk, Gerrit I., and Wendy K. Silverman. Anxiety Disorders. Edited by Thomas H. Ollendick, Susan W. White, and Bradley A. White. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190634841.013.20.
Full textBook chapters on the topic "Biais cognitifs – Diagnostic"
Howard, Jonathan. "Hindsight Bias and Outcome Bias." In Cognitive Errors and Diagnostic Mistakes, 247–64. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_14.
Full textHoward, Jonathan. "Information Bias." In Cognitive Errors and Diagnostic Mistakes, 303–6. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_17.
Full textHoward, Jonathan. "Omission Bias." In Cognitive Errors and Diagnostic Mistakes, 321–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_19.
Full textHoward, Jonathan. "Overconfidence Bias." In Cognitive Errors and Diagnostic Mistakes, 351–67. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_21.
Full textHoward, Jonathan. "Representativeness Bias." In Cognitive Errors and Diagnostic Mistakes, 425–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_24.
Full textHoward, Jonathan. "Financial Bias." In Cognitive Errors and Diagnostic Mistakes, 109–38. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_8.
Full textHoward, Jonathan. "Blind Spot Bias." In Cognitive Errors and Diagnostic Mistakes, 525–35. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_29.
Full textPat, Croskerry. "Cognitive Bias Mitigation: Becoming Better Diagnosticians." In Diagnosis, 257–87. Boca Raton : Taylor & Francis, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315116334-15.
Full textHoward, Jonathan. "Selection Bias and Endowment Effect." In Cognitive Errors and Diagnostic Mistakes, 457–66. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_26.
Full textHoward, Jonathan. "Bandwagon Effect and Authority Bias." In Cognitive Errors and Diagnostic Mistakes, 21–56. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93224-8_3.
Full textReports on the topic "Biais cognitifs – Diagnostic"
Peterson, Bradley S., Joey Trampush, Margaret Maglione, Maria Bolshakova, Morah Brown, Mary Rozelle, Aneesa Motala, et al. ADHD Diagnosis and Treatment in Children and Adolescents. Agency for Healthcare Research and Quality (AHRQ), March 2024. http://dx.doi.org/10.23970/ahrqepccer267.
Full textNewman-Toker, David E., Susan M. Peterson, Shervin Badihian, Ahmed Hassoon, Najlla Nassery, Donna Parizadeh, Lisa M. Wilson, et al. Diagnostic Errors in the Emergency Department: A Systematic Review. Agency for Healthcare Research and Quality (AHRQ), December 2022. http://dx.doi.org/10.23970/ahrqepccer258.
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