ARTIFICIAL INTELLIGENCE IN MEDICINE: "EARLY DISEASE DETECTION MODELS"

Abstract

ABSTRACT : This thesis shows the application of artificial intelligence (AI) in medicine, focusing on the development and evaluation of early disease detection models. We investigate the potential of AI to analyze complex medical datasets, including imaging, genomics, and clinical records, to identify subtle patterns indicative of disease onset before conventional diagnostic methods. The research encompasses the design of novel machine learning algorithms, feature engineering techniques, and validation strategies to optimize model performance and clinical utility. We address challenges such as data heterogeneity, bias, and interpretability to ensure robust and equitable application of AI in early disease detection, with the ultimate goal of improving patient outcomes and healthcare efficiency.