Authors: Shruthi Singh
Abstract: Electronic Health Records (EHRs) have revolutionized healthcare by digitizing patient information, enabling comprehensive data capture across clinical settings. The integration of machine learning (ML) techniques with EHR data holds immense potential for predictive healthcare, facilitating early diagnosis, risk stratification, personalized treatment, and improved patient outcomes. This paper explores how machine learning algorithms applied to EHR datasets can transform healthcare delivery by enabling predictive analytics, clinical decision support, and population health management. Key challenges such as data quality, interoperability, privacy, and model interpretability are discussed alongside emerging solutions. The future of predictive healthcare lies in harnessing the synergy of EHRs and AI to advance precision medicine, reduce costs, and enhance healthcare accessibility.
DOI: http://doi.org/10.61137/ijsret.vol.8.issue6.561
