Machine learning predicts improvement of functional outcomes in traumatic brain injury patients after inpatient rehabilitation.
Front Rehabil Sci
; 3: 1005168, 2022.
Article
in En
| MEDLINE
| ID: mdl-36211830
ABSTRACT
Survivors of traumatic brain injury (TBI) have an unpredictable clinical course. This unpredictability makes clinical resource allocation for clinicians and anticipatory guidance for patients difficult. Historically, experienced clinicians and traditional statistical models have insufficiently considered all available clinical information to predict functional outcomes for a TBI patient. Here, we harness artificial intelligence and apply machine learning and statistical models to predict the Functional Independence Measure (FIM) scores after rehabilitation for traumatic brain injury (TBI) patients. Tree-based algorithmic analysis of 629 TBI patients admitted to a large acute rehabilitation facility showed statistically significant improvement in motor and cognitive FIM scores at discharge.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Type of study:
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
Front Rehabil Sci
Year:
2022
Document type:
Article
Affiliation country:
United States