Abstract
In this day and age with technology advancing rapidly, it has become possible to store and access tremendous amount of data at the touch of one’s fingertips. Diligent utilization of patient medical records is essential for making judicious clinical decisions and for providing health care of the highest order. Public health concerns are steadily increasing as a result of the expanding population. Hence, there is an exponential surge in the amount of data that requires processing. Big data tools that can efficiently minimize the processing time and eliminate errors are the need of the hour. The clinical decision support system (CDSS) is one such advancement that has been gaining traction in recent years. CDSS can be defined as “any electronic or non-electronic active knowledge system specifically designed to aid in clinical decision-making, in which parameters of individual patient health can be used to intelligently filter and generate patient-specific evaluations and assessments which serve as recommendations to clinicians during treatment, thereby enhancing patient care.” CDSS is an information technology tool that, depending on the patient’s input data, can give the assessments, prognosis and medical recommendations based on the nature of the medical condition. CDSS is a major player in the field of artificial intelligence in medicine. It is a revolutionary method that has the potential to galvanize the field of health care, as evidenced by statistical analysis and the multiple successful case studies that have been documented in this chapter.
Keywords
- Public health care
- Medicine
- Clinical decision support system (CDSS)
- Fuzzy logic
- Data mining
- Bayesian networks
- Genetic algorithms
- Hybrid systems
- Clinical outcomes
- Adverse drug events (ADEs)
- Electronic health records (EHR)
- Diagnosis decision support system (DDSS)
- Artificial intelligence
- Machine learning
- Decision-making
- Case-based reasoning system (CBR)
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The authors express their appreciation to the RSST trust Bangalore for their continuous support and encouragement. The corresponding author expresses his sincere thanks to all other authors whose valuable contribution and important comments made the manuscript to this form.
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The authors have no conflict of interest. There was also no problem related to funding. All authors have contributed equally with their valuable comments which made the manuscript to this form.
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Gupta, P.K. et al. (2021). An Overview of Clinical Decision Support System (CDSS) as a Computational Tool and Its Applications in Public Health. In: Kumar, R., Paiva, S. (eds) Applications in Ubiquitous Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-35280-6_5
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