Clinical Decision Support System Design Issues

In healthcare, computer science plays an important role in analysing and diagnosing medical problems and diseases. Artificial intelligence (AI) has revolutionised medical science. Nowadays, AI is in high demand in medicinal science. This paper describes important design issues related to the characteristics of the clinical decision support system (CDSS) and the methodologies used for its implementation. It defines how they are figured out for diagnosis of diseases and symptoms. These case-studies lead us to CDSS and help figure out the most optimal methodology and the best solution for diagnosing a medical problem. This paper aims to survey important CDSS research works and presents a case-study based on the analysis and comparison of various methodologies used in CDSSs. We find that every methodology has some good and some bad aspects. Different methodologies for CDSSs use various parameters for solving medical diagnosis problems. Some methodologies are very good in one domain, whereas others are good in a different domain, but the aim of all methodologies is the same, i.e., to solve medical diagnosis problems.