ROLE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN HEALTHCARE FOR EARLY DISEASE PREDICTION

• Author Information

  Nishant, Abhay, Navneet Sharma, Neha Kumari, Daljeet Masih

• Nishant, Abhay, Navneet Sharma, Neha Kumari, Daljeet Masih
• ROLE OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN HEALTHCARE FOR EARLY DISEASE PREDICTION

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing the healthcare and pharmaceutical industries by offering advanced capabilities in data-driven decision-making, prediction, and automation. AI encompasses technologies that replicate human cognitive functions, while ML, a crucial subset, enables systems to learn from data and make autonomous decisions. In healthcare, AI-ML integration is transforming diagnostic accuracy, treatment planning, and patient monitoring. Among their most impactful applications is early disease prediction, particularly in chronic illnesses such as diabetes, cancer, and cardiovascular diseases, where early intervention can significantly improve prognosis and reduce healthcare costs. In the pharmaceutical sector, AI-ML technologies are reshaping traditional drug discovery and development models that have historically been time-consuming and costly. These tools facilitate faster target identification, streamline compound optimization, and enable personalized medicine approaches, thereby reducing development timelines and expenditures. Evidence from the IQVIA Institute for Human Data Science underscores the role of AI in cutting research and development costs and enhancing the precision of therapeutic development. Collectively, AI and ML are ushering in a new era of precision, efficiency, and cost-effectiveness in both clinical practice and pharmaceutical innovation.

Keywords: Artificial Intelligence, Machine Learning, Early Disease Prediction, Drug Development, Personalized Medicine, Healthcare Innovation.