AI-Based Clinical Decision Support Systems: A Study on Healthcare Improvement
Abstract
Riya Divekar and Ramesh D Jadhav
Clinical Decision Support Systems (CDSS) play a crucial role in modern healthcare by assisting clinicians in making accurate and timely decisions. With the integration of Artificial Intelligence (AI), CDSS has evolved into an advanced system capable of analyzing large volumes of patient data, identifying patterns, and generating evidence-based recommendations. AI-driven CDSS enhances diagnostic accuracy, predicts potential diseases, and supports personalized treatment planning. These systems help reduce medical errors, improve patient safety, and optimize clinical workflows. However, despite these advantages, several challenges remain, including concerns related to data privacy, lack of transparency in AI algorithms, and difficulties in integrating these systems into existing healthcare infrastructures. This study examines the working mechanisms, applications, advantages, and limitations of AI-based CDSS while also identifying gaps and future research directions. The findings emphasize the importance of developing reliable, secure, and explainable AI systems to ensure effective adoption inhealthcare.