Artificial Intelligence-Based Decision Support Systems for Early Disease Diagnosis

Abstract

Early disease diagnosis is a critical factor in improving patient outcomes and reducing healthcare costs. Artificial intelligence-based decision support systems have emerged as powerful tools for assisting clinicians in diagnosing diseases at an early stage by analyzing complex medical data. These systems utilize machine learning, deep learning, and data analytics techniques to identify patterns that may not be easily detectable through conventional clinical evaluation. This paper examines the role of artificial intelligence-based decision support systems in early disease diagnosis. Key system architectures, data sources, and diagnostic applications are discussed, along with their benefits and limitations. The study highlights the potential of AI-driven decision support systems to enhance diagnostic accuracy, support clinical decision-making, and improve the efficiency of healthcare delivery.