Implementing AI in Healthcare for Predictive Diagnostics

Implementing AI in Healthcare for Predictive Diagnostics

Yash S. Sawant1, Rahul U. Pawar2, Sanika C. Joshi3

1,2,3Post-Graduate Student, MCA Department, Finolex Academy of Management and Technology, Ratnagiri, Maharashtra, India.

Abstract

Artificial Intelligence (AI) is revolutionizing modern healthcare, especially in the field of predictive diagnostics. By leveraging advanced computational models and vast clinical datasets, AI has the capability to detect diseases early, predict disease progression, and optimize patient treatment strategies. The integration of machine learning (ML), deep learning (DL), and natural language processing (NLP) enables AI systems to analyze data from diverse sources such as electronic health records (EHRs), medical imaging, genetic profiles, and wearable devices. This paper delves into the applications, roles, and real-world case studies demonstrating AI's impact in predictive diagnostics. It also examines the significant challenges faced in implementing AI systems, explores ethical considerations, and outlines future directions for advancing AI-driven diagnostics in global healthcare systems.

Keywords : Artificial Intelligence, Predictive Diagnostics, Machine Learning, Deep Learning, Healthcare Analytics, Medical Imaging