Artificial Intelligence In Early Disease Diagnosis: Transforming General Medicine Through Predictive Analytics

Abstract

Artificial Intelligence (AI) has emerged as one of the most transformative technologies in modern healthcare, enabling early disease detection, predictive analytics, and clinical decision support. This research explores how AI-driven tools and algorithms are revolutionizing general medicine through improved diagnostic accuracy, faster decision-making, and enhanced patient outcomes. By integrating large-scale health data, machine learning (ML) models, and pattern recognition, AI systems are capable of detecting subtle signs of diseases such as diabetes, cardiovascular disorders, and cancer before clinical symptoms manifest. The study employs a mixed-method approach involving quantitative analysis of AI-assisted diagnostic data and qualitative assessment through physician and patient surveys. Findings reveal that AI significantly reduces diagnostic errors, shortens the time to diagnosis, and increases the precision of preventive health strategies. Despite challenges related to data privacy, algorithm bias, and integration into clinical workflows, AI demonstrates enormous potential in transforming general medicine from reactive to predictive care.