Filters








935 Hits in 5.3 sec

A Bayesian framework for early risk prediction in traumatic brain injury

Shikha Chaganti, Andrew J. Plassard, Laura Wilson, Miya A. Smith, Mayur B. Patel, Bennett A. Landman, Martin A. Styner, Elsa D. Angelini
2016 Medical Imaging 2016: Image Processing  
Early detection of risk is critical in determining the course of treatment in traumatic brain injury (TBI).  ...  Herein, we propose a Bayesian framework with mutual information-based forward feature selection to handle this type of data.  ...  This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN.  ... 
doi:10.1117/12.2217306 pmid:27127331 pmcid:PMC4845965 dblp:conf/miip/ChagantiPWSPL16 fatcat:cup4ktiiffem5jjgca2lcnadt4

A hierarchical Bayesian model to predict APOE4 genotype and the age of Alzheimer's disease onset

Francis Hane, Carolyn Augusta, Owen Bai, Yun Li
2018 PLoS ONE  
In this work we use a hierarchical Bayesian paradigm to introduce a theoretical framework to determine an individual's Apolipoprotein ε4 (APOE4) genotype, which heavily influences both the age of onset  ...  We disseminated our Alzheimer's predictive tool online at  ...  CIHR) for their support of this research.  ... 
doi:10.1371/journal.pone.0200263 pmid:30001420 pmcid:PMC6042730 fatcat:cxnbjqqanjc7pinema5fboguey

Nursing Education, Trauma and Care in the Intensive Care

Marianne Frieri
2017 International Archives of Nursing and Health Care  
In addition, head injury prevention, traumatic brain injury, a survey of nurses' perceptions in caring for patients with traumatic brain injury, outcomes and interventions for patients undergoing cardiac  ...  Post operative cardio-thoracic surgical patients experiencing nursing bedside handover, a standardized infant positioning assessment tool and a bedside education program by registered nurses and highly  ...  In addition, head injury prevention, traumatic brain injury, a survey of nurses' perceptions in caring for patients with traumat- • Page 3 of 6 • Frieri et al.  ... 
doi:10.23937/2469-5823/1510076 fatcat:qz4tqwf23vhtrad5pe7jd2vbei

Accurate risk stratification for development of organ/space surgical site infections after emergent trauma laparotomy

Shuyan Wei, Charles Green, Lillian S. Kao, Brandy B. Padilla-Jones, Van Thi Thanh Truong, Charles E. Wade, John A. Harvin
2019 Journal of Trauma and Acute Care Surgery  
Risk stratification for OS-SSI in these patients could guide promising, but unproven, interventions for OS-SSI prevention, such as more frequent dosing of intraoperative antibiotics or direct peritoneal  ...  Retrospective review was performed on a prospectively maintained database of emergent trauma laparotomies from 2011 to 2016. Patient demographics and risk factors for OS-SSI were collected.  ...  Acknowledgments Disclosures: SW is supported by a T32 fellowship (grant no. 5T32GM008792) from NIGMS. Authors report no conflicts of interest.  ... 
doi:10.1097/ta.0000000000002143 pmid:30531329 pmcid:PMC7004798 fatcat:cxupqnrdnvghlhwx2hphq6owkq

A Functional Model for Structure Learning and Parameter Estimation in Continuous Time Bayesian Network: An Application in Identifying Patterns of Multiple Chronic Conditions [article]

Syed Hasib Akhter Faruqui, Adel Alaeddini, Jing Wang, Carlos A. Jaramillo
2021 arXiv   pre-print
of the existing methods in the literature for both short-term (one-year ahead) and long-term (multi-year ahead) predictions.  ...  Bayesian networks are powerful statistical models to study the probabilistic relationships among set random variables with major applications in disease modeling and prediction.  ...  FIGURE 1 . 1 Illustration of the functional CTBN for 5 MCC including Traumatic Brain Injury (TBI), Back Pain (BaPa), Post Traumatic Stress Disorder (PTSD), Depression (Depr), and Substance Abuse (SuAb)  ... 
arXiv:2007.15847v2 fatcat:wx6s5ggdrbc55bwupnz4cyf2kq

Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network

Syed Hasib Akhter Faruqui, Adel Alaeddini, Carlos A. Jaramillo, Jennifer S. Potter, Mary Jo Pugh, Mark Webber Miller
2018 PLoS ONE  
Department of Veterans Affairs for a period of five years, we compare the performance of the proposed unsupervised Bayesian network in comparison with those of Bayesian networks developed based on supervised  ...  and semisupervised learning approaches, as well as multivariate probit regression, multinomial logistic regression, and latent regression Markov mixture clustering focusing on traumatic brain injury (  ...  a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 Introduction For nearly a decade, clinicians caring for Veterans with traumatic brain injury (TBI) have described multimorbidity among those  ... 
doi:10.1371/journal.pone.0199768 pmid:30001371 pmcid:PMC6042705 fatcat:pzdp7ppjtrg2vplwewkmtmutkm

A Functional Model for Structure Learning and Parameter Estimation in Continuous Time Bayesian Network: An Application in Identifying Patterns of Multiple Chronic Conditions

Syed Hasib Akhter Faruqui, Adel Alaeddini, Jing Wang, Carlos A. Jaramillo, Mary Jo Pugh
2021 IEEE Access  
of the existing methods in the literature for both short-term (one-year ahead) and long-term (multi-year ahead) predictions.  ...  Bayesian networks are powerful statistical models to study the probabilistic relationships among sets of random variables with significant applications in disease modeling and prediction.  ...  Illustration of the functional CTBN for 5 MCC including Traumatic Brain Injury (TBI), Back Pain (BaPa), Post Traumatic Stress Disorder (PTSD), Depression (Depr), and Substance Abuse (SuAb) based on the  ... 
doi:10.1109/access.2021.3122912 pmid:35371895 pmcid:PMC8975131 fatcat:v4usqdpgyberjk2lsvuhtritya

Front Matter: Volume 10572

Jorge Brieva, Juan David García, Natasha Lepore, Eduardo Romero
2017 13th International Conference on Medical Information Processing and Analysis  
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  using a Base 36 numbering system employing both numerals and letters.  ...  in early childhood 10572 0P Altered network topology in pediatric traumatic brain injury 10572 0Q Statistical shape (ASM) and appearance (AAM) models for the segmentation of the cerebellum in fetal  ... 
doi:10.1117/12.2310208 dblp:conf/sipaim/X17 fatcat:5mpaoft6nfcwrbrauhmpsgzemy

Adaptive and platform trials in remote damage control resuscitation

Juliana Tolles, Roger J. Lewis
2018 Journal of Trauma and Acute Care Surgery  
This leads to an increased risk of a failed trial.  ...  The traditional approach to clinical trial design requires assuming precise values for multiple unknown parameters, resulting in a trial design that is unlikely to perform well if one or more of those  ...  There is no less need for investigation of novel therapeutics in traumatic injury than in oncology.  ... 
doi:10.1097/ta.0000000000001904 pmid:29554037 fatcat:abubto2q3fdfxgrhxjwe3c3hzq

Trajectories and predictors of return to work after traumatic limb injury – a 2-year follow-up study

Wen-Hsuan Hou, Ching-Fan Sheu, Huey-Wen Liang, Ching-Lin Hsieh, Yen Lee, Hung-Yi Chuang, Yan-Tzong Cheng
2012 Scandinavian Journal of Work, Environment and Health  
Methods A total of 804 participants were recruited during hospital admission for a 2-year prospective study.  ...  An understanding of how different factors contribute to increasing the likelihood of RTW for injured workers in each trajectory group should aid policy-making in worker-oriented vocational rehabilitation  ...  Previous presentation Part of this manuscript was presented in the Annual Conference of Taiwan Public Health Association, Taipei, Taiwan, 15 October 2011.  ... 
doi:10.5271/sjweh.3287 pmid:22388635 fatcat:s77fbgtgancizicgwgc7lw5jfy

Not just data: A method for improving prediction with knowledge

Barbaros Yet, Zane Perkins, Norman Fenton, Nigel Tai, William Marsh
2014 Journal of Biomedical Informatics  
The method is illustrated by a case study into the prediction of acute traumatic coagulopathy (ATC), a disorder of blood clotting that significantly increases the risk of death following traumatic injuries  ...  In this paper, we present a methodology for developing Bayesian network (BN) models that predict and reason with latent variables, using a combination of expert knowledge and available data.  ...  Another important cause of traumatic coagulopathy is a catastrophic brain injury. These injuries seem to effect coagulation via a different mechanism to ATC.  ... 
doi:10.1016/j.jbi.2013.10.012 pmid:24189161 fatcat:yhzstmuobjhylhrnf6jngavk2i

Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury

Noémi Kreif, Richard Grieve, Iván Díaz, David Harrison
2015 Health Economics  
centres, for patients with acute traumatic brain injury.  ...  ill patients with traumatic brain injury (TBI).  ...  We are grateful to Eric Polley for help in using the Super Learner and to Mark van der Laan for helpful comments.  ... 
doi:10.1002/hec.3189 pmid:26059721 pmcid:PMC4744663 fatcat:ukyayvvgyjgl5j5a4qqxqyevzm

Mixture Model Framework for Traumatic Brain Injury Prognosis Using Heterogeneous Clinical and Outcome Data [article]

Alan D. Kaplan, Qi Cheng, K. Aditya Mohan, Lindsay D. Nelson, Sonia Jain, Harvey Levin, Abel Torres-Espin, Austin Chou, J. Russell Huie, Adam R. Ferguson, Michael McCrea, Joseph Giacino (+3 others)
2021 arXiv   pre-print
Prognoses of Traumatic Brain Injury (TBI) outcomes are neither easily nor accurately determined from clinical indicators.  ...  In this work, we develop a method for modeling large heterogeneous data types relevant to TBI.  ...  We would like to thank Grant Bouquet from Lawrence Livermore National Laboratory for conversations on software tools for probabilistic modeling.  ... 
arXiv:2012.12310v3 fatcat:uml4bvpf7zf37mx767xhhu4rpe

What predicts persisting social impairment following pediatric traumatic brain injury: contribution of a biopsychosocial approach

Vicki Anderson, Stephen J. C. Hearps, Cathy Catroppa, Miriam H. Beauchamp, Nicholas P. Ryan
2022 Psychological Medicine  
Despite increasing recognition of post-injury behavioral and social problems, there exists a paucity of research regarding the incidence of social impairment, and factors predicting risk and resilience  ...  Background Psychosocial deficits, such as emotional, behavioral and social problems, reflect the most common and disabling consequences of pediatric traumatic brain injury (TBI).  ...  The authors would like to thank the participating children and parents for their support of this study.  ... 
doi:10.1017/s0033291722000186 pmid:35189999 fatcat:5wntocdvarfqfpy37zj3p4omfa

A Latent Class Analysis of Pathological-Gambling Criteria Among High School Students

Grace Kong, Jack Tsai, Suchitra Krishnan-Sarin, Dana A. Cavallo, Rani A. Hoff, Marvin A. Steinberg, Loreen Rugle, Marc N. Potenza
2014 Journal of addiction medicine  
Abstracts of these reports are available now 301 unique articles this week The SafetyLit Foundation has been designated a not-for-profit 501 (c)(3) public charity by the US IRS Please consider making a  ...  Click on the title of a report to view the full citation and abstract.  ...  Accident analysis using count data for unsignalized intersections in Malaysia Cost of traumatic brain injury in New Zealand: Evidence from a population-based study The impact of pediatric traumatic brain  ... 
doi:10.1097/adm.0000000000000074 pmid:25275877 pmcid:PMC4667944 fatcat:3fkt7q7qafadznw323jlclpjnu
« Previous Showing results 1 — 15 out of 935 results