Relevant bibliographies by topics / Brain injury – diagnosis

Academic literature on the topic 'Brain injury – diagnosis'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Brain injury – diagnosis"

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Дюсембеков, Е. К., А. Р. Халимов, Л. Н. Танашева, И. Т. Курмаев, А. С. Жайлаубаева, А. В. Николаева, and М. Ж. Мирзабаев. "BRAIN DEATH DIAGNOSIS IN SEVERE TRAUMATIC BRAIN INJURY (TBI)." Vestnik, no. 3 (December 15, 2021): 102–6. http://dx.doi.org/10.53065/kaznmu.2021.79.37.019.

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Проведено клинико-неврологическое и инструментальное исследование смерти мозга у 23 пациентов с тяжелой черепно-мозговой травмой за 2020 год. Результаты исследования показали, что летальность в первые 72 часа была в 14 случаях - 60,9%. Досуточная летальность составила 9 случаев - 39,1 %. Пациенты трудоспособного возраста составили 83%. В большинстве случаев клиническая картина смерти мозга осложнялась наличием травм лица, спонтанными или индуцированными автоматизмами, ушибом легких при сочетанной травме. В данной статье описаны виды клинических исследований, используемых в диагностике смерти мозга, в сложных случаях дополнительных подтверждающих тестов. Research has been done of 23 patients with а severe traumatic brain injury (TBI) in 2020. Outcomes of our research have indicated mortality in the first 72 hours was in 14 cases - 60,9%.And the first day lethality was 9 cases - 39,1%. The significant quantity of working age patients amounts to 83%. Generally, brain death in any patient with catastrophic brain injury and a bedside exam consistent with brain death complicated by facial injuries, spontaneous or induced automatism, lungs contusion with concomitant injury. The article describes types of clinical examination, used in the definition of brain death. In complicated cases, supplementary confirm tests.
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Machado, Calixto. "Diagnosis of brain death." Neurology International 2, no. 1 (February 25, 2010): 2. http://dx.doi.org/10.4081/ni.2010.e2.

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Brain death (BD) should be understood as the ultimate clinical expression of a brain catastrophe characterized by a complete and irreversible neurological stoppage, recognized by irreversible coma, absent brainstem reflexes, and apnea. The most common pattern is manifested by an elevation of intracranial pressure to a point beyond the mean arterial pressure, and hence cerebral perfusion pressure falls and, as a result, no net cerebral blood flow is present, in due course leading to permanent cytotoxic injury of the intracranial neuronal tissue. A second mechanism is an intrinsic injury affecting the nervous tissue at a cellular level which, if extensive and unremitting, can also lead to BD. We review here the methodology of diagnosing death, based on finding any of the signs of death. The irreversible loss of cardio-circulatory and respiratory functions can cause death only when ischemia and anoxia are prolonged enough to produce an irreversible destruction of the brain. The sign of such loss of brain functions, that is to say BD diagnosis, is fully reviewed.
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Mysiw, W. Jerry, and Rebecca D. Jackson. "Differential diagnosis of agitation following brain injury." NeuroRehabilitation 5, no. 3 (October 1, 1995): 197–204. http://dx.doi.org/10.3233/nre-1995-5302.

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FitzGerald, David B., and Charles E. Levy. "Delayed Diagnosis of Severe Traumatic Brain Injury." American Journal of Physical Medicine & Rehabilitation 94, no. 4 (April 2015): e33. http://dx.doi.org/10.1097/phm.0000000000000250.

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Ling, Geoffrey S. F., Scott A. Marshall, and David F. Moore. "DIAGNOSIS AND MANAGEMENT OF TRAUMATIC BRAIN INJURY." CONTINUUM: Lifelong Learning in Neurology 16 (December 2010): 27–40. http://dx.doi.org/10.1212/01.con.0000391451.30299.bc.

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Fins, J. J. "Diagnosis and Treatment of Traumatic Brain Injury." JAMA: The Journal of the American Medical Association 283, no. 18 (May 10, 2000): 2392. http://dx.doi.org/10.1001/jama.283.18.2392.

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Powell, Janet M., Joseph V. Ferraro, Sureyya S. Dikmen, Nancy R. Temkin, and Kathleen R. Bell. "Accuracy of Mild Traumatic Brain Injury Diagnosis." Archives of Physical Medicine and Rehabilitation 89, no. 8 (August 2008): 1550–55. http://dx.doi.org/10.1016/j.apmr.2007.12.035.

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Mysiw, W. "Differential diagnosis of agitation following brain injury." Neurorehabilitation 5, no. 3 (July 1995): 197–204. http://dx.doi.org/10.1016/1053-8135(95)00117-q.

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Carter-Allison, Samantha N., Sebastian Potter, and Katharine Rimes. "Diagnosis Threat and Injury Beliefs After Mild Traumatic Brain Injury." Archives of Clinical Neuropsychology 31, no. 7 (August 22, 2016): 727–37. http://dx.doi.org/10.1093/arclin/acw062.

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Macmillan, C. SA, J. M. Wild, P. JD Andrews, J. M. Wardlaw, I. Marshall, J. Cannon, and P. A. Jones. "ACCURATE BRAIN INJURY DIAGNOSIS USING CHEMICAL SHIFT MAGNETIC RESONANCE IMAGING IN ACUTE BRAIN INJURY." Journal of Neurosurgical Anesthesiology 10, no. 4 (October 1998): 294. http://dx.doi.org/10.1097/00008506-199810000-00153.

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Dissertations / Theses on the topic "Brain injury – diagnosis"

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McGrath, Joanna Ruth. "Fear following brain injury." Thesis, Oxford Brookes University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325266.

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Kinkela, Jessica H. "Diagnosis Threat in Mild Traumatic Brain Injury." Ohio University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1223597555.

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Carter-Allison, Samantha Natalie. "Diagnosis threat and injury beliefs after mid traumatic brain injury." Thesis, King's College London (University of London), 2015. https://kclpure.kcl.ac.uk/portal/en/theses/diagnosis-threat-and-injury-beliefs-after-mid-traumatic-brain-injury(c6ba3d52-13d9-46ea-aeee-d34ed2e43943).html.

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Background: Diagnosis threat is a form of stereotype threat, where individuals with a history of mild traumatic brain injury (mTBI) have shown performance decrements on cognitive tasks, owing to negative expectancies around cognitive ability elicited by cues in the environment. This study systematically reviews experimental studies to gauge the presence/absence of an effect of diagnosis threat on neuropsychological task performance in mTBI. It also investigates whether methodological variation and methodological quality contribute to variation in study findings. Method: A systematic search of four online databases (Medline, PyscINFO, SportDISCUS, PsycEXTRA) was conducted to identify diagnosis threat studies that employed an experimental paradigm. Neuropsychological test outcomes were extracted, along with information on inclusion criteria, mTBI diagnostic criteria, participant characteristics and study design. Methodological quality was assessed using modified Scottish Intercollegiate Guidelines Network (SIGN) criteria. Results: A total of nine studies were identified. Evidence for diagnosis threat was found, although there was considerable heterogeneity across study results. The most robust finding was the impact of diagnosis threat on the cognitive domain of attention/working memory. No clear associations between methodological variation, methodological quality and study outcome were noted. Conclusions: The review found evidence for diagnosis threat, although the strength of this effect may be smaller than previously thought. Although there was heterogeneity across elements of study design, there was no obvious relationship between these factors and outcome. However, the substantial variation makes comparison difficult. These issues are similar to findings in other examinations of stereotype threat. Further research is needed to replicate findings and add clarity to the impact of diagnosis threat on both objective and subjective measures, and to further investigate the role of possible moderating variables. A more formal meta-analysis in the area may also be helpful to clarify findings in the research field. Future studies should aim to create established operational definitions and outcomes to improve consistency and comparability between studies.
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Scholtz, Brendon P. "Effects of Cautioning and Education in the Detection of Malingered Mild Traumatic Brain Injury." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5247/.

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This study examined the effectiveness of cautioning and education on simulating a mild traumatic brain injury on several neuropsychological measures. The measures used included the Word Memory Test (WMT), Wechsler Adult Intelligence Scales® - Third Edition (WAIS®-III), Wechsler Memory Scales®-3rd Edition instrument (WMS®-III), 16-item version of the Rey Memory Test, and a self-report symptom checklist. Five experimental groups were used including clinical and non-clinical controls, as well as three simulation groups. The design and implementation of this study also attempted to correct several methodological short comings of prior research by increasing the incentives for participants, expanding the generalizability of findings and examining research compliance and participant self-perception through debriefing. Discriminant analysis was utilized to determine if specific functions existed that would correctly classify and distinguish each experimental group. Several discriminant functions had at least moderate canonical correlations and good classification accuracy. Results also include utility estimates given projected varying base rates of malingering.
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Gesler, Toni L. "Differential diagnosis of head injury and depression in adults." Virtual Press, 2005. http://liblink.bsu.edu/uhtbin/catkey/1343468.

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A differential diagnosis between head injury and depression is critical to ensure proper treatment and appropriate interventions. Knowledge about this can only aid counseling psychologists' work with this population and, identifying a measure that can assist in this process is essential. The purpose of this study is to measure the utility of the Dean — Woodcock Neuropsychological Assessment System (D-WNAS) in distinguishing individuals with head injury from those who have a primary diagnosis of depression, and general neurological impairment. Participants included 433 adults (222 males, 211 females) between the ages 20-55 years of age (mean = 35.3 years, SD = 10.97 years) from the Midwestern United States. During the individual's treatment in the neuropsychological laboratory, each person was administered the following: the Dean-Woodcock Structured Interview (Dean & Woodcock, 1999), mental status exam, the Woodcock Johnson — Revised Tests of Cognitive Ability (WJ-R COG; Woodcock & Johnson, 1989b), the Woodcock Johnson — Revised Tests of Achievement (WJ-R ACH; Woodcock & Johnson, 1989a), and the Dean-Woodcock Sensory Motor Battery (DWSMB; Dean & Woodcock, 1999). This study indicates that responses to D-WNAS can be used to reliably classify adults into groups of depression, head injury, and general neuropsychological impairment. In particular, responses to the D-WSMB portion of the D-WNAS can be used to reliably classify adults into groups of depression, head injury, and general neuropsychological impairment. Classification results revealed that the original grouped cases were classified with 62.6 % (p < .001) accuracy and with 73.2% overall accuracy when the head injury and general neurological impairment groups were combined and compared to depression and normative groups. The WJ-R COG and WJ-R ACH were not as reliable as the D-WSMB at predicting group membership.
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Clements, Andrea D. "Mild Traumatic Brain Injury in Multiple Trauma Patients: the Problem of Delayed Diagnosis." Digital Commons @ East Tennessee State University, 1997. https://dc.etsu.edu/etsu-works/7217.

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Excerpt: With all that is currently known about symptoms that indicate mild traumatic brain injury (MTBI), it is unfortunate that many individuals go undiagnosed for long periods of time after sustaining such an injury.
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Riddick, Amy H. "The Utility of Depression Screening Measures After Traumatic Brain Injury." Also available to VCU users online at:, 2007. http://hdl.handle.net/10156/1439.

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Mercer, Walt N. (Walt Neilson). "Performance of Brain-Injured versus Non-Brain-Injured Individuals on Three Versions of the Category Test." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278878/.

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To date, no research exists examining criterion-related validity of alternate, computerized forms of the Category Test. The intent of this study was to address criterion-related validity of three full forms of the Category Test. In that, the goal was to examine equivalency of each version in their ability to differentiate brain-injured from non-brain-injured individuals. Forty-nine (N = 49) healthy adults and 45 (N = 45) brain-injured adults were tested using three versions of the Category Test, the BDI, and the WAIS-R NI. ANOVA indicated no significant differences between versions of the Category Test or an interaction between Category Test version and group membership on the total error score. MANOVA performed between versions of the Category Test and Subtest error scores indicated significant differences between versions on Subtest 3 and Subtest 6. Group membership (brain-injured v. non-brain-injured) produced a significant main effect on all subtests of the Category Test except Subtest 2. Several exploratory analyses were performed examining the relationship between neuropsychological impairment, group membership based on Category Test error scores, and the WAIS-R NI. Clinical applications, such as the use of serial testing to index neurorehabilitation gains, were discussed.
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Collingwood, Lisa M. (Lisa Marie). "Performance of Psychiatric and Head Injury Patients on the General Neuropsychological Deficit Scales." Thesis, University of North Texas, 1997. https://digital.library.unt.edu/ark:/67531/metadc278771/.

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Reitan and Wolfson's General Neuropsychological Deficit Scale and Left and Right Neuropsychological Deficit Scales were applied to Halstead-Reitan test data of individuals with psychotic or substance abuse disorders with and without a head injury.
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Wang, Silun, and 王思倫. "Diffusion tensor MR imaging as a biomarker for the evaluation of whitematter injury in rodent models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43085416.

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Books on the topic "Brain injury – diagnosis"

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1953-, Silver Jonathan M., Yudofsky Stuart C, and Hales Robert E, eds. Neuropsychiatry of traumatic brain injury. Washington, DC: American Psychiatric Press, 1994.

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Radomski, Mary Vining, Margaret M. Weightman, Pauline A. Mashima, and Carole R. Roth. Mild traumatic brain injury rehabilitation toolkit. Fort Sam Houston, TX: Borden Institute, 2014.

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Minor traumatic brian injury handbook: Diagnosis and treatment. Boca Raton: CRC Press, 2000.

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Mild traumatic brain injury: Symptom validity assessment and malingering. New York: Springer Pub. Co., 2013.

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Mild traumatic brain injury: The guidebook. Raleigh, NC]: [Lulu Enterprises Inc.], 2010.

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Textbook of traumatic brain injury. 2nd ed. Washington, DC: American Psychiatric Pub., 2011.

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Granacher, Robert P. Traumatic brain injury: Methods for clinical and forensic neuropsychiatric assessment. 2nd ed. Boca Raton: CRC Press/Taylor & Francis Group, 2008.

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Ann, Roberts Mary, Murph Jody R, Phillips George 1971-, and Sheehan William, eds. Mild traumatic brain injury: Episodic symptoms and treatment. San Diego: Plural Pub., 2011.

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1949-, Bigler Erin D., ed. Traumatic brain injury: Mechanisms of damage, assessment, intervention, and outcome. Austin, Tex: Pro-Ed, 1990.

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Pimental, Patricia A. Mini inventory of right brain injury: Examiner's manual. 2nd ed. Austin, Tex: PRO-ED, 2000.

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Book chapters on the topic "Brain injury – diagnosis"

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Le, Tuong H., Shirley I. Stiver, and Alisa D. Gean. "Imaging Diagnosis of TBI." In Traumatic Brain Injury, 15–48. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-0-387-87887-4_2.

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Samuel, Tina L., and Karen M. Barlow. "Pediatric Concussion Diagnosis, Management, and Rehabilitation." In Traumatic Brain Injury, 383–97. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22436-3_19.

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Mensah, Seth A., and Michael P. Kerr. "Depression and Traumatic Brain Injury." In Depression in Neurologic Disorders: Diagnosis and Management, 189–205. Oxford, UK: Wiley-Blackwell, 2012. http://dx.doi.org/10.1002/9781118348093.ch15.

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Tong, Karen A., Udochukwu E. Oyoyo, Barbara A. Holshouser, Stephen Ashwal, and L. Santiago Medina. "Traumatic Brain Injury: Evidence-Based Neuroimaging." In Evidence-Based Neuroimaging Diagnosis and Treatment, 357–84. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-3320-0_23.

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Hirasawa, Yasusuke. "Differential Diagnosis from Spinal and Brain Disorders." In Treatment of Nerve Injury and Entrapment Neuropathy, 151–59. Tokyo: Springer Japan, 2002. http://dx.doi.org/10.1007/978-4-431-67883-0_14.

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Ko, Hyun-Yoon. "Dual Diagnosis of Traumatic Brain Injury with Spinal Cord Injury." In Management and Rehabilitation of Spinal Cord Injuries, 753–61. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0228-4_39.

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Fernandez, Andres, Kristine H. O’Phelan, and M. Ross Bullock. "Traumatic Brain Injury: Evidence-Based Medicine, Diagnosis, and Treatment." In Textbook of Neurointensive Care, 591–99. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5226-2_27.

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Yoshihara, M., A. Tsunoda, K. Sato, S. Kanayama, and A. Calderon. "Differential Diagnosis of NPH and Brain Atrophy Assessed by Measurement of Intracranial and Ventricular CSF Volume with 3D FASE MRI." In Intracranial Pressure and Neuromonitoring in Brain Injury, 371–74. Vienna: Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6475-4_107.

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Fargen, Kyle M., and David W. Pincus. "Pediatric Traumatic Brain Injury: Evidence-Based Medicine, Diagnosis, Treatment, and Complications." In Textbook of Neurointensive Care, 601–18. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5226-2_28.

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"Cognitive Disorders: Diagnosis and Treatment in Traumatic Brain Injury." In Traumatic Brain Injury, 599–636. CRC Press, 2016. http://dx.doi.org/10.1201/9781439849828-24.

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Conference papers on the topic "Brain injury – diagnosis"

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Gasimzade, G. Sh. "Early diagnosis of traumatic brain injury." In Global science. Development and novelty. НИЦ «Л-Журнал», 2019. http://dx.doi.org/10.18411/gdsn-25-12-2019-17.

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Edquilang, David, and Jeff Feng. "A Novel Headset System Synchronizing Vision and EEG testing for a Rapid Assessment and Diagnosis of Concussions and Other Brain Injuries." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002125.

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Millions of concussions happen each year in the US alone. A proportionally large number of these concussions are due to high impact sports injury. Currently, there exists no solution to quickly monitor brain functions and test the oculomotor functions of individuals who have suffered a traumatic brain injury in order to diagnose them as having suffered a concussion. What is presently done to diagnose concussions is a CT scan or MRI, which are lengthy procedures to schedule, set up, and conduct; and furthermore, takes additional time to analyze the results in order to arrive at a diagnosis. This prolongation of the diagnosing process is inherently problematic since the longer time it takes between time of injury and time of diagnosis, there is greater risk of decisions and actions which can worsen damage to the brain. The sooner a concussion can be diagnosed, the sooner and better the treatment can be performed for recovery. In order to ameliorate this issue, we seek to develop a device to perform the function of diagnosis and monitoring of brain activity in a more rapid and timely manner. Literature review into the anatomy of vestibular and ocular brain functions was performed; as well as research into various testing and monitoring methodologies of these vestibular and ocular functions. One such method that has proven to be a reliable method for diagnosis is Vestibular Ocular Motor Screening (VOMS), which is a visual and balance test performed by a doctor with a patient. Further research was also done into existing technologies whose functionalities would allow the device in order to perform brain monitoring, visual testing, and ultimately diagnosis; namely EEG, VR, and infrared eye tracking. Currently, very few devices on the market take advantage of these technologies together for medical uses. A device incorporating these technologies together allows would allow for more consistent administering of visual tests and real-time monitoring of brain activity. With a functional prototype, user testing is to be performed in order to assess the function and viability of the device.
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Mobley, Joel, Paul M. Kasili, Stephen J. Norton, and Tuan Vo-Dinh. "Application of ultrasonic techniques for brain injury diagnosis." In BiOS '99 International Biomedical Optics Symposium, edited by Tuan Vo-Dinh, Warren S. Grundfest, David A. Benaron, Steven T. Charles, Richard D. Bucholz, and Michael W. Vannier. SPIE, 1999. http://dx.doi.org/10.1117/12.351520.

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Li, Lin, Dheeraj Chahal, James Z. Wang, Mark A. Eckert, and Carl Lozar. "Online Brain Image Database System for Diagnosis of Subtle Brain Injury." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5515703.

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Standvoss, Kai, Lisa Goerke, Tanja Crijns, Timo van Niedek, Natali Alfonso Burgos, Démian Janssen, Joris van Vugt, et al. "Cerebral microbleed detection in traumatic brain injury patients using 3D convolutional neural networks." In Computer-Aided Diagnosis, edited by Kensaku Mori and Nicholas Petrick. SPIE, 2018. http://dx.doi.org/10.1117/12.2294016.

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Albert, Bruno, Jingjing Zhang, Alexandre Noyvirt, Rossitza Setchi, Haldor Sjaaheim, Svetla Velikova, and Frode Strisland. "Automatic EEG processing for the early diagnosis of Traumatic Brain Injury." In 2016 World Automation Congress (WAC). IEEE, 2016. http://dx.doi.org/10.1109/wac.2016.7582957.

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Connolly, Thomas J. M., and J. Keith Clutter. "Modeling Head Motion During Explosive Events to Assess Brain Injury Severity in a Battlefield Environment." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-43391.

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The occurrence of blast induced brain injury in individuals serving in Iraq and Afghanistan is dramatically higher than in past conflicts. This has been attributed in part to the prevalence of roadside improvised explosive devices, or IEDs. There is a call from the military medical community to reduce the reliance on victim self-reporting as the primary diagnosis technique to determine the likelihood of brain injury after a blast. This study demonstrates the utility of computational modeling in establishing clear criteria that denotes the probability of cerebral contusion and, thus, brain injury. Computational fluid dynamics (CFD) is used to establish the environment from a full range of threats. This is combined with bond graph modeling of varying levels of fidelity to estimate the dynamics of the skull and brain. Results clearly show that a boundary exists in the threat parameter space that determines whether brain injury occurs.
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Balakrishnan, Amulya, and Sowmya Patapati. "Automation of traumatic brain injury diagnosis through an IoT-based embedded systems framework." In 2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON). IEEE, 2017. http://dx.doi.org/10.1109/uemcon.2017.8249087.

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Sjaaheim, Haldor, Bruno Albert, Rossi Setchi, and Frode Strisland. "A portable medical system for the early diagnosis and treatment of Traumatic Brain Injury." In 2014 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2014. http://dx.doi.org/10.1109/smc.2014.6974307.

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Wang, Yuye, Guoqiang Wang, Degang Xu, Bozhou Jiang, Meilan Ge, Limin Wu, Chuanyan Yang, et al. "Diagnosis of blast-induced traumatic brain injury in rat based on terahertz spectroscopy of serum." In Infrared, Millimeter-Wave, and Terahertz Technologies VII, edited by Xi-Cheng Zhang, Masahiko Tani, and Cunlin Zhang. SPIE, 2020. http://dx.doi.org/10.1117/12.2575630.

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Reports on the topic "Brain injury – diagnosis"

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Cheng, Yu-Chung N. Development and Testing of Iron Based Phantoms as Standards for the Diagnosis of Microbleeds and Oxygen Saturation with Applications in Dementia, Stroke, and Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada601806.

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Bergold, Peter. Interhemispheric Information Transfer: A New Diagnostic Method for Mild Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, October 2011. http://dx.doi.org/10.21236/ada613511.

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Sharma, Pushpa, Neil Grunberg, He Li, Erin Berry, and Brandi Benford. Mitochondrial Damage: A Diagnostic and Metabolic Approach in Traumatic Brain Injury and Post-Traumatic Disorder. Fort Belvoir, VA: Defense Technical Information Center, January 2013. http://dx.doi.org/10.21236/ada579698.

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Spencer, Trina, Kerstin Tönsing, and Shakila Dada. Augmentative and Alternative Communication (AAC) Interventions that Promote Labeling, Commenting, and Telling: A Systematic Review Protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2022. http://dx.doi.org/10.37766/inplasy2022.4.0078.

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Review question / Objective: The aim of this systematic review is to identify and describe the augmentative and alternative communication (AAC) interventions that improve the labeling, commenting, and telling skills of children with communication disabilities. To that end, the following questions will be addressed: What is the quality and quantity of research investigating AAC interventions to promote labeling, commenting, and telling skills of children with communication disabilities? Which (if any) AAC interventions have sufficient empirical evidence to support their recommendation in practice for teaching children with communication disabilities labeling, commenting, and telling skills? Condition being studied: Speech is the primary modality of communication and socialization. However, not all individuals develop functional speech due to a variety of developmental or acquired disabilities, such as autism spectrum disorders (ASD), cerebral palsy (CP), or traumatic brain Injury. Although diagnoses vary, all these individuals share the condition of being unable to meet all the communication needs that others without disabilities typically meet through speech. Such Individuals are typically described as having complex communication needs or a severe communication disorder, or as requiring augmentative and alternative communication (Von Tetzchner & Basil, 2011).
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5

Newman-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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Objectives. Diagnostic errors are a known patient safety concern across all clinical settings, including the emergency department (ED). We conducted a systematic review to determine the most frequent diseases and clinical presentations associated with diagnostic errors (and resulting harms) in the ED, measure error and harm frequency, as well as assess causal factors. Methods. We searched PubMed®, Cumulative Index to Nursing and Allied Health Literature (CINAHL®), and Embase® from January 2000 through September 2021. We included research studies and targeted grey literature reporting diagnostic errors or misdiagnosis-related harms in EDs in the United States or other developed countries with ED care deemed comparable by a technical expert panel. We applied standard definitions for diagnostic errors, misdiagnosis-related harms (adverse events), and serious harms (permanent disability or death). Preventability was determined by original study authors or differences in harms across groups. Two reviewers independently screened search results for eligibility; serially extracted data regarding common diseases, error/harm rates, and causes/risk factors; and independently assessed risk of bias of included studies. We synthesized results for each question and extrapolated U.S. estimates. We present 95 percent confidence intervals (CIs) or plausible range (PR) bounds, as appropriate. Results. We identified 19,127 citations and included 279 studies. The top 15 clinical conditions associated with serious misdiagnosis-related harms (accounting for 68% [95% CI 66 to 71] of serious harms) were (1) stroke, (2) myocardial infarction, (3) aortic aneurysm and dissection, (4) spinal cord compression and injury, (5) venous thromboembolism, (6/7 – tie) meningitis and encephalitis, (6/7 – tie) sepsis, (8) lung cancer, (9) traumatic brain injury and traumatic intracranial hemorrhage, (10) arterial thromboembolism, (11) spinal and intracranial abscess, (12) cardiac arrhythmia, (13) pneumonia, (14) gastrointestinal perforation and rupture, and (15) intestinal obstruction. Average disease-specific error rates ranged from 1.5 percent (myocardial infarction) to 56 percent (spinal abscess), with additional variation by clinical presentation (e.g., missed stroke average 17%, but 4% for weakness and 40% for dizziness/vertigo). There was also wide, superimposed variation by hospital (e.g., missed myocardial infarction 0% to 29% across hospitals within a single study). An estimated 5.7 percent (95% CI 4.4 to 7.1) of all ED visits had at least one diagnostic error. Estimated preventable adverse event rates were as follows: any harm severity (2.0%, 95% CI 1.0 to 3.6), any serious harms (0.3%, PR 0.1 to 0.7), and deaths (0.2%, PR 0.1 to 0.4). While most disease-specific error rates derived from mainly U.S.-based studies, overall error and harm rates were derived from three prospective studies conducted outside the United States (in Canada, Spain, and Switzerland, with combined n=1,758). If overall rates are generalizable to all U.S. ED visits (130 million, 95% CI 116 to 144), this would translate to 7.4 million (PR 5.1 to 10.2) ED diagnostic errors annually; 2.6 million (PR 1.1 to 5.2) diagnostic adverse events with preventable harms; and 371,000 (PR 142,000 to 909,000) serious misdiagnosis-related harms, including more than 100,000 permanent, high-severity disabilities and 250,000 deaths. Although errors were often multifactorial, 89 percent (95% CI 88 to 90) of diagnostic error malpractice claims involved failures of clinical decision-making or judgment, regardless of the underlying disease present. Key process failures were errors in diagnostic assessment, test ordering, and test interpretation. Most often these were attributed to inadequate knowledge, skills, or reasoning, particularly in “atypical” or otherwise subtle case presentations. Limitations included use of malpractice claims and incident reports for distribution of diseases leading to serious harms, reliance on a small number of non-U.S. studies for overall (disease-agnostic) diagnostic error and harm rates, and methodologic variability across studies in measuring disease-specific rates, determining preventability, and assessing causal factors. Conclusions. Although estimated ED error rates are low (and comparable to those found in other clinical settings), the number of patients potentially impacted is large. Not all diagnostic errors or harms are preventable, but wide variability in diagnostic error rates across diseases, symptoms, and hospitals suggests improvement is possible. With 130 million U.S. ED visits, estimated rates for diagnostic error (5.7%), misdiagnosis-related harms (2.0%), and serious misdiagnosis-related harms (0.3%) could translate to more than 7 million errors, 2.5 million harms, and 350,000 patients suffering potentially preventable permanent disability or death. Over two-thirds of serious harms are attributable to just 15 diseases and linked to cognitive errors, particularly in cases with “atypical” manifestations. Scalable solutions to enhance bedside diagnostic processes are needed, and these should target the most commonly misdiagnosed clinical presentations of key diseases causing serious harms. New studies should confirm overall rates are representative of current U.S.-based ED practice and focus on identified evidence gaps (errors among common diseases with lower-severity harms, pediatric ED errors and harms, dynamic systems factors such as overcrowding, and false positives). Policy changes to consider based on this review include: (1) standardizing measurement and research results reporting to maximize comparability of measures of diagnostic error and misdiagnosis-related harms; (2) creating a National Diagnostic Performance Dashboard to track performance; and (3) using multiple policy levers (e.g., research funding, public accountability, payment reforms) to facilitate the rapid development and deployment of solutions to address this critically important patient safety concern.
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