Determining the probability of survival after injury is important as it can inform triage, clinical research and audit. A number of methods have been reported for determining the probability of survival after injury. However, these have shortcomings and thus further developments are needed to improve their reliability and accuracy. In this study, a Bayesian method called Predictive Statistical Diagnosis (PSD) was developed to determine probability of survival in 4124 adults (age: mean = 67.9 years, standard deviation = 21.6 years) with traumatic brain injuries (TBI). In total, 86.2% of cases had survived and 13.8% of cases had not survived their injuries. The parameters considered as inputs to PSD were age, abbreviated injury score (AIS), G...
Objective: Clinical features such as those included in the Glasgow Coma Scale (GCS) score, pupil r...
Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial pressure...
Our aim was to create simple and largely scalable machine learning-based algorithms that could predi...
Determining the probability of survival after injury is important as it can inform triage, clinical ...
The aim of this study is to design, develop and evaluate artificial intelligence and statistical tec...
Trauma brain injury (TBI) is the most common cause of death and disability in young adults. A method...
The probability or likelihood of survival in trauma injuries is a clinically important parameter for...
A preliminary computational analysis of a number of factors affecting the probability of survival in...
Background Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable predi...
Background Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable predi...
BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable pred...
BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability world-wide. The ...
Introduction For making reliable decisions, practitioners need to estimate uncertainties that exist...
ObjectiveWe aimed to explore the added value of common machine learning (ML) algorithms for predicti...
Background Traumatic brain injury (TBI), which occurs commonly worldwide, is among the more costly o...
Objective: Clinical features such as those included in the Glasgow Coma Scale (GCS) score, pupil r...
Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial pressure...
Our aim was to create simple and largely scalable machine learning-based algorithms that could predi...
Determining the probability of survival after injury is important as it can inform triage, clinical ...
The aim of this study is to design, develop and evaluate artificial intelligence and statistical tec...
Trauma brain injury (TBI) is the most common cause of death and disability in young adults. A method...
The probability or likelihood of survival in trauma injuries is a clinically important parameter for...
A preliminary computational analysis of a number of factors affecting the probability of survival in...
Background Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable predi...
Background Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable predi...
BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability. A reliable pred...
BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability world-wide. The ...
Introduction For making reliable decisions, practitioners need to estimate uncertainties that exist...
ObjectiveWe aimed to explore the added value of common machine learning (ML) algorithms for predicti...
Background Traumatic brain injury (TBI), which occurs commonly worldwide, is among the more costly o...
Objective: Clinical features such as those included in the Glasgow Coma Scale (GCS) score, pupil r...
Intensive care for patients with traumatic brain injury (TBI) aims to optimize intracranial pressure...
Our aim was to create simple and largely scalable machine learning-based algorithms that could predi...