Paper
28 February 2012 Using connectionist models to determine decision making strategy of pathology residents reading dermatopathology digital slides
Claudia Mello-Thoms, Gregory Gardner
Author Affiliations +
Abstract
Theories of the processes involved in medical decision making have long been formulated in an attempt to understand medical reasoning. Historically medical training has relied on the 'forward reasoning strategy, where trainees are instructed to collect all diagnostic evidence before formulating any hypotheses. However, more recently, studies have determined that medical experts do not rely on such time consuming strategies, but instead quickly generate diagnostic hypotheses and then proceed to collect diagnostic evidence to confirm or to dismiss each hypothesis. In light of this, medical training has been switched to rely on the hypothetical deductive' approach, in which trainees are instructed to mimic the experts and generate diagnostic hypotheses first and then gather diagnostic evidence to sort out the hypotheses. Both reasoning models have shortcomings, as identification of many irrelevant findings adds too much noise to the diagnostic process in the 'forward reasoning' case, whereas identification of too many competing hypotheses generates too large a problem space in the 'hypothetical deductive' approach. In this paper we will use connectionist modeling to simulate the decision making strategies of Pathology residents 'before' and 'after' they undergo a well-known difficult rotation, that in Dermatopathology. We will seek to identify changes in the reasoning patterns of the residents as a result of formal training in the domain. We hypothesize that 'before' undertaking the rotation residents will rely on the 'forward reasoning' approach, whereas 'after' their rotation they are more likely to use the 'hypothetical deductive' reasoning.
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Claudia Mello-Thoms and Gregory Gardner "Using connectionist models to determine decision making strategy of pathology residents reading dermatopathology digital slides", Proc. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 83181U (28 February 2012); https://doi.org/10.1117/12.912572
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KEYWORDS
Diagnostics

Pathology

Performance modeling

Statistical modeling

Cognitive modeling

Skin

Medical imaging

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