Quantitative and Qualitative Approaches to Reasoning under Uncertainty in Medical Decision Making

Medical decision making frequently requires the effective management and communication of uncertainty and risk. However a tension exists between classical probability theory, which is precise and rigorous but which people find non-intuitive and difficult to use, and qualitative approaches which are ad hoc but can be more versatile and easily comprehensible. In this paper we review a range of approaches to uncertainty management, then describe a logical approach, argumentation, which subsumes qualitative as well as quantitative representations and has a clear formal semantics. The approach is illustrated and evaluated in five decision support applications.

[1]  J. Fox,et al.  Knowledge acquisition for expert systems: experience in leukaemia diagnosis. , 1985, Methods of information in medicine.

[2]  Anthony Hunter,et al.  Applications of Uncertainty Formalisms , 1998, Lecture Notes in Computer Science.

[3]  Understanding probability words by constructing concrete mental models , 2020, Proceedings of the Twenty First Annual Conference of the Cognitive Science Society.

[4]  Elizabeth C. Hirschman,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[5]  John Fox,et al.  Representation of Chemical Structures in Knowledge-Based Systems: The StAR System , 1997, J. Chem. Inf. Comput. Sci..

[6]  James Shanteau,et al.  Psychological characteristics of expert decision makers , 1987 .

[7]  P. Todd,et al.  Simple Heuristics That Make Us Smart , 1999 .

[8]  R. Gregory,et al.  Subjective Probability , 1957, Nature.

[9]  J Austoker,et al.  Computer support for interpreting family histories of breast and ovarian cancer in primary care: comparative study with simulated cases , 2000, BMJ : British Medical Journal.

[10]  Shawn P. Curley,et al.  Applying a cognitive perspective to probability construction. , 1994 .

[11]  Andrew S. Coulson,et al.  RAGs: A Novel Approach to Computerized Genetic Risk Assessment and Decision Support from Pedigrees , 2001, Methods of Information in Medicine.

[12]  Gregory M. Provan,et al.  The Sensitivity of Belief Networks to Imprecise Probabilities: An Experimental Investigation , 1996, Artif. Intell..

[13]  Philip N. Judson,et al.  Representation of Chemical Structures in Knowledge‐Based Systems: The StAR System. , 1997 .

[14]  W. Thompson,et al.  The genetic attributable risk of breast and ovarian cancer , 1996, Cancer.

[15]  Paul R. Cohen,et al.  Heuristic reasoning about uncertainty: an artificial intelligence approach , 1984 .

[16]  Jonathan Evans,et al.  Rationality and reasoning , 1996 .

[17]  R. Carpenter,et al.  Multistage scoring system for identifying infants at risk of unexpected death. , 1977, Archives of disease in childhood.

[18]  J. Fox,et al.  Evaluation of computer support for prescribing (CAPSULE) using simulated cases , 1997, BMJ.

[19]  J. Chang,et al.  Right-sided congenital diaphragmatic herniae presenting as pleural effusions in the newborn: dangers and pitfalls. , 1978, Archives of disease in childhood.

[20]  M O'Neil,et al.  Evaluating and validating very large knowledge-based systems. , 1990, Medical informatics = Medecine et informatique.

[21]  Paul J. Krause,et al.  Acceptability of arguments as 'logical uncertainty' , 1993, ECSQARU.

[22]  John Fox,et al.  Safe and sound - artificial intelligence in hazardous applications , 2000 .

[23]  Andrew Todd-Pokropek,et al.  The development and evaluation of CADMIUM: a prototype system to assist in the interpretation of mammograms , 1999, Medical Image Anal..

[24]  John Fox,et al.  Arguments, Contradicitions and Practical Reasoning , 1992, ECAI.

[25]  J. Fox,et al.  Alternatives to Bayes? , 1980, Methods of Information in Medicine.

[26]  Michael Clarke,et al.  Symbolic and Quantitative Approaches to Reasoning and Uncertainty , 1991, Lecture Notes in Computer Science.

[27]  J. Emery,et al.  A systematic review of the literature exploring the role of primary care in genetic services. , 1999, Family practice.

[28]  Alan Bundy,et al.  Symbolic and Quantitative Approaches to Reasoning and Uncertainty , 1993 .