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Computer-assisted decision making in medicine.

J C Kunz, E H Shortliffe, B G Buchanan

    The Journal of Medicine and Philosophy
    |May 1, 1984
    PubMed
    Summary
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    This review explores five medical computer-assisted decision-making (CADM) approaches, highlighting that combining techniques, especially artificial intelligence (AI), offers promising advancements in healthcare decision support.

    Area of Science:

    • Medical Informatics
    • Artificial Intelligence in Medicine
    • Clinical Decision Support Systems

    Background:

    • Computer-assisted decision making (CADM) is crucial in modern medicine.
    • Several distinct paradigms exist for CADM, each with unique strengths and weaknesses.
    • Evaluating these paradigms is essential for advancing medical decision support.

    Purpose of the Study:

    • To review and compare five major CADM paradigms.
    • To identify the strengths and limitations of each approach.
    • To explore the potential of combining different CADM techniques.

    Main Methods:

    • Review of clinical algorithms.
    • Analysis of statistical methods for patient data.
    • Examination of mathematical models for physical processes.

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  • Evaluation of decision analysis frameworks.
  • Assessment of symbolic reasoning and artificial intelligence (AI) in medicine.

    • Main Results:

    • No single CADM technique is universally optimal for all medical applications.
    • Each of the five reviewed paradigms (clinical algorithms, statistical analysis, mathematical models, decision analysis, AI) has specific advantages and disadvantages.
    • Promising research is emerging that integrates multiple CADM techniques.

    Conclusions:

    • The inherent power of symbolic reasoning and AI offers significant potential for medical decision support.
    • Combining different CADM techniques can lead to more robust and versatile solutions.
    • Future advancements in CADM will likely involve synergistic integration of diverse methodologies.