Impact of Machine Learning-Driven Predictive Models on Patient Outcomes in Modern Healthcare Systems

Traditional healthcare systems often struggle to meet the diverse needs of patients, leading to inefficiencies and
less-than-optimal outcomes. The integration of machine learning (ML) is transforming healthcare by focusing on value-based care and enabling personalized, effective treatments. Modern healthcare devices are equipped with applications that collect and store comprehensive patient data, forming the basis for ML-driven predictive models.
This research investigates the transformative impact of ML in healthcare, highlighting its ability to improve patient care and optimize resource allocation. A proposed predictive model utilizes patient data and key parameters to forecast diseases, leveraging extensive datasets from diverse populations. These tools empower healthcare providers to identify and manage high-risk cases proactively, improving outcomes while streamlining care delivery processes.