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Clinical Decision Support System for Early Disease Detection and Management: Statistics-Based Early Disease Detection

Clinical Decision Support System for Early Disease Detection and Management: Statistics-Based Early Disease Detection

Likewin Thomas, Manoj Kumar M. V., Annappa B.
Copyright: © 2021 |Pages: 41
ISBN13: 9781799890232|ISBN10: 1799890236|EISBN13: 9781799890249
DOI: 10.4018/978-1-7998-9023-2.ch051
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MLA

Thomas, Likewin, et al. "Clinical Decision Support System for Early Disease Detection and Management: Statistics-Based Early Disease Detection." Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering, edited by Information Resources Management Association, IGI Global, 2021, pp. 1035-1075. https://doi.org/10.4018/978-1-7998-9023-2.ch051

APA

Thomas, L., M. V., M. K., & B., A. (2021). Clinical Decision Support System for Early Disease Detection and Management: Statistics-Based Early Disease Detection. In I. Management Association (Ed.), Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering (pp. 1035-1075). IGI Global. https://doi.org/10.4018/978-1-7998-9023-2.ch051

Chicago

Thomas, Likewin, Manoj Kumar M. V., and Annappa B. "Clinical Decision Support System for Early Disease Detection and Management: Statistics-Based Early Disease Detection." In Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering, edited by Information Resources Management Association, 1035-1075. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-9023-2.ch051

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Abstract

Medical error is an adverse event of a failure in healthcare management, causing unintended injuries. Proper clinical care can be provided by employing a suitable clinical decision support system (CDSS) for healthcare management. CDSS assists the clinicians in identifying the severity of disease at the time of admission and predicting its progression. In this chapter, CDSS was developed with the help of statistical techniques. Modified cascade neural network (ModCNN) was built upon the architecture of cascade-correlation neural network (CCNN). ModCNN first identifies the independent factors associated with disease and using that factor; it predicts its progression. A case progressing towards severity can be given better care, avoiding later stage complications. Performance of ModCNN was evaluated and compared with artificial neural network (ANN) and CCNN. ModCNN showed better accuracy than other statistical techniques. Thus, CDSS developed in this chapter is aimed at providing better treatment planning by reducing medical error.

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