This paper reports the analysis of data on traumatic brain injury using a probabilistic graphical modeling technique known as reconstructability analysis (RA). The analysis shows the flexibility, power, and comprehensibility of RA modeling, which is well-suited for mining biomedical data. One finding of the analysis is that education is a confounding variable for the Digit Symbol Test in discriminating the severity of concussion; another - and anomalous - finding is that previous head injury predicts improved performance on the Reaction Time test. This analysis was exploratory, so its findings require follow-on confirmatory tests of their generalizability
This thesis focuses on identifying factors that could be used to predict recovery following concussi...
Concussions are a serious public health problem, with significant healthcare costs and risks. One of...
Traumatic brain injury (TBI) is one of the most common causes of death and disability worldwide, yet...
This paper reports the analysis of data on traumatic brain injury using a probabilistic graphical mo...
Most data analyses are confirmatory, but exploratory studies can find unexpected non-linear & many-v...
A short presentation of an analysis of data from Dr. Megan Preece on traumatic brain injury, the fir...
Clinical studies are expensive & time-consuming. Typically in these studies specific hypotheses are ...
Abstract The use of precision medicine is poised to increase in complex injuries such as traumatic b...
Traumatic brain injuries contribute to a high degree of morbidity and mortality in society. To study...
AbstractA concussion is an invisible and poorly understood mild traumatic brain injury (mTBI) that c...
“Concussions represent a growing health concern and are challenging to diagnose and manage. Roughly ...
The practical application of machine learning in medicine has been a budding field of study to take ...
ObjectiveThere is no civilian TBI database that captures patients in all settings of the care-contin...
A computational simulation model calculates recovery trajectories following traumatic brain injury (...
Traumatic brain injury (TBI) is a major public health problem. Despite considerable research deciphe...
This thesis focuses on identifying factors that could be used to predict recovery following concussi...
Concussions are a serious public health problem, with significant healthcare costs and risks. One of...
Traumatic brain injury (TBI) is one of the most common causes of death and disability worldwide, yet...
This paper reports the analysis of data on traumatic brain injury using a probabilistic graphical mo...
Most data analyses are confirmatory, but exploratory studies can find unexpected non-linear & many-v...
A short presentation of an analysis of data from Dr. Megan Preece on traumatic brain injury, the fir...
Clinical studies are expensive & time-consuming. Typically in these studies specific hypotheses are ...
Abstract The use of precision medicine is poised to increase in complex injuries such as traumatic b...
Traumatic brain injuries contribute to a high degree of morbidity and mortality in society. To study...
AbstractA concussion is an invisible and poorly understood mild traumatic brain injury (mTBI) that c...
“Concussions represent a growing health concern and are challenging to diagnose and manage. Roughly ...
The practical application of machine learning in medicine has been a budding field of study to take ...
ObjectiveThere is no civilian TBI database that captures patients in all settings of the care-contin...
A computational simulation model calculates recovery trajectories following traumatic brain injury (...
Traumatic brain injury (TBI) is a major public health problem. Despite considerable research deciphe...
This thesis focuses on identifying factors that could be used to predict recovery following concussi...
Concussions are a serious public health problem, with significant healthcare costs and risks. One of...
Traumatic brain injury (TBI) is one of the most common causes of death and disability worldwide, yet...