Year: 2025
Type: article
Abstract: Traumatic brain injury (TBI) is a critical health issue, requiring an accurate and timely prognosis to inform medical interventions. This paper focuses on machine learning techniques to predict patients' outcomes, specifically targeting the Indian demographic. Key metrics such as age, time since injury, Glasgow Coma Scale (GCS), and Glasgow Outcome Scale (GOS) are utilized to assess damage severity and forecast mortality and morbidity. By integrating a Random Forest Classifier for mortality prediction and a Random Forest Regressor for morbidity estimation, the system provides a required outcome according to the input of the patient's condition. The models are trained on simulated data and integrated into a web-based platform, enabling automated predictions and user-friendly interfaces for healthcare providers. This approach gives the diagnostic accuracy, supports critical decision-making, and promotes timely medical responses, ultimately improving patient care outcomes.
Author: E Bharath
Institution: Ballari Institute of Technology & Management
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4410259390