Machine Learning in Predictive Healthcare: Transforming Patient Outcomes

Prof. Kim Chen

Abstract


Machine learning (ML) has become a pivotal technology in predictive healthcare, offering significant potential to improve patient outcomes. This paper explores the application of ML algorithms in predicting disease onset, progression, and patient responses to treatments. By reviewing recent advancements and case studies, the study evaluates the accuracy and effectiveness of ML models in early diagnosis, personalized treatment plans, and preventive care. The findings suggest that ML can revolutionize healthcare by enabling more proactive and tailored interventions, ultimately enhancing patient care and reducing healthcare costs.

 

 

 


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