AI-Driven Clinical Decision Support Systems: Revolutionizing Healthcare With Predictive Models
Sanjeev Kukreti, Anurag Shrivastava, Rakesh Chandrashekar, K. Pushpa Rani, Arti Badhoutiya, Sorabh Lakhanpal
Abstract
The integration of artificial intelligence (AI) into Clinical Decision Support Systems (CDSS) is changing the face of healthcare by allowing AI powered predictive, data driven insights, enabling medical practitioners to prolong their diagnosis and treatment planning. To make better and faster clinical judgements, CDSS based on AI using machine learning techniques such as ensemble methods and deep learning is discussed in this paper. He said most of the focus is on models that can predict future events, diagnose plagues and deliver tailored treatment programs sifting through mountains of health care data, such as genetics, medical imaging and EHRs. Some of the main problems we work with as we implement AI driven CDSS is its data privacy, model interpretability and integration to current healthcare processes. In addition this study summarizes recent advances in artificial intelligence (AI), enabling real time analysis and making real time decisions to improve patient outcomes and reduce workloads of healthcare personnel. Case examples that employ AI-CDSS to identify diseases, optimize treatments and predict risk are provided to show how they can change the face of clinical practice. Finally, we explore where AI healthcare may be going from here with a focus on the importance of deploying these systems with patient well being in mind and with full compliance to the relevant regulations.