ArticleFrontiers in rehabilitation sciences2022
Machine learning predicts improvement of functional outcomes in traumatic brain injury patients after inpatient rehabilitation.
Article in Frontiers in rehabilitation sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 12 citations in OpenAlex.
- Artificial Intelligence in Physical Therapy: A Narrative Review of Artificial Intelligence Applications Across the Patient and Client Management Model.Health science reports · 2026Article
- A Hybrid Bidirectional Deep Learning Model Using HRV for Prediction of ICU Mortality Risk in TBI Patients.Journal of healthcare informatics research · 2025Article
- Prediction of Clinically Significant Improvements During the Interdisciplinary Intensive Outpatient Program for Traumatic Brain Injury Using Machine Learning.Annals of biomedical engineering · 2025Article
- Setting the foundation for a national collaborative learning health system in acute TBI rehabilitation: CARE4TBI Year 1 experience.Learning health systems · 2025Article
- Traumatic Brain Injury and Artificial Intelligence: Shaping the Future of Neurorehabilitation-A Review.Life (Basel, Switzerland) · 2025Review
- Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation.Frontiers in rehabilitation sciences · 2025Article
- Predictive Modeling of Long-Term Care Needs in Traumatic Brain Injury Patients Using Machine Learning.Diagnostics (Basel, Switzerland) · 2024Article
- Enhancing hospital course and outcome prediction in patients with traumatic brain injury: A machine learning study.The neuroradiology journal · 2024Article
- Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.Frontiers in artificial intelligence · 2024Article
- Traumatic Brain Injury Rehabilitation Outcome Prediction Using Machine Learning Methods.Archives of rehabilitation research and clinical translation · 2023Article
- Machine Learning Approach for the Prediction of In-Hospital Mortality in Traumatic Brain Injury Using Bio-Clinical Markers at Presentation to the Emergency Department.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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