A survey of clinical decision support systems

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Authors: Vinayak Gupta, Yajnaseni Dash, Dinesh Kumar, Naween Kumar, Sudhir Chandra Sarangi
Cited by: 0

Abstract

Clinical decision support systems (CDSSs) are now well integrated within modern healthcare organizations, where they enjoy the responsibility of improving diagnostics and therapeutic approaches and, thus, patient care. This chapter aims to give a detailed analysis of the changes in artificial intelligence (AI) in the development and operations of CDSS. It emphasizes significant innovations in AI technologies, especially in machine learning, deep learning, and natural language processing, due to their increased ability to analyze data and improve decision-making systems. The chapter also outlines the historical development of the CDSS from the traditional rule-based systems to the use of advanced AI systems in the growth of the CDSS, which has enhanced the proficiency of extensive complex data analysis. This includes chief complaints/presenting complaints, electronic medical records as well as electronic health records (EHRs), medical images and images for diagnosis, and genomic data, among others, because today&s;s advanced CDSSs can not only assist and enhance the clinicians’ decision-making process but also boost the way the patient receives his or her treatment—which in a sense makes an important step toward better healthcare. AI is still slowly but surely gaining a foothold within the framework of CDSSs, thus opening the way to a progressive orientation toward the principles of personalized and prescriptive medicine based on data.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Electronic Health Records Systems Artificial Intelligence in Healthcare

Publication details

Journal / source
CRC Press eBooks
Pages
188–198
Publication date
2 February 2026
Language
EN
Document type
Book chapter