Decision Support Systems Machine Learning

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What is the difference between Decision Support System and ...

    https://cs.stackexchange.com/questions/13871/what-is-the-difference-between-decision-support-system-and-machine-learning
    I have started reading about Decision Support Systems which according to wikipedia is "a computer-based information system that supports business or organizational decision-making activities". I have seen papers suggesting intelligent decision support systems, does that means a DSS necessarily utilizes Machine Learning ?

Benefits and Risks of Machine Learning Decision Support ...

    https://jamanetwork.com/journals/jama/fullarticle/2666494
    Dec 19, 2017 · To the Editor Machine learning decision support systems (ML-DSS) have been touted as a key driver of major changes in the way medicine is practiced.1 Although most articles describe the benefits of incorporating these techniques, Dr Cabitza and colleagues2 rightly cautioned that there are potential...Cited by: 3

Medical decision support systems based on machine learning

    http://ir.uiowa.edu/cgi/viewcontent.cgi?article=1469&context=etd
    MEDICAL DECISION SUPPORT SYSTEMS BASED ON MACHINE LEARNING METHODS by Chih-Lin Chi An Abstract Of a thesis submitted in partial ful llment of the requirements for the Doctor of Philosophy degree

Machine learning based decision support systems (DSS) for ...

    https://link.springer.com/article/10.1007/s10462-017-9552-8
    Mar 25, 2017 · The current review contributes with an extensive overview of decision support systems in diagnosing heart diseases in clinical settings. The investigators independently screened and abstracted studies related to heart diseases-based clinical decision support system (DSS) published until 8-June-2015 in PubMed, CINAHL and Cochrane Library.Cited by: 10

Intelligent Decision Support Systems Based on Machine ...

    https://www.hindawi.com/journals/sp/si/295240/cfp/
    Intelligent decision support systems (IDSSs) are widely used in various computer science applications for intelligent decision-making. To implement these IDSSs, machine learning algorithms and diverse programming paradigms and frameworks are required. Machine learning and prediction algorithms are abundant in nature and produce variable results.



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