Year: 2025
Type: article
Abstract: The integration of predictive analysis into healthcare has the potential to transform patient care, clinical decision-making, and operational efficiency.By leveraging advanced machine learning algorithms, big data analytics, and real-time monitoring, predictive models can identify disease risks, forecast patient outcomes, and optimize resource allocation.These techniques enable healthcare providers to shift from reactive treatments toward proactive and preventive care, improving patient safety and reducing costs.Predictive analysis can be applied across various domains, including early disease detection, personalized treatment plans, hospital readmission prediction, and epidemic outbreak forecasting.However, challenges such as data privacy, model interpretability, and integration with existing healthcare systems must be addressed to ensure reliability and trust.This paper explores the role of predictive analysis in building smarter healthcare systems, highlighting its benefits, key applications, and future directions for achieving more efficient, patient-centered care.
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4413851473