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Table 1 Rating rubric suggested by Smith et al. (0 = None, 1 = Some, 2 = Appropriate) [5] and additional category “patient name”

From: Automatic analysis of summary statements in virtual patients - a pilot study evaluating a machine learning approach

Category Scoring Description
Use of semantic qualifiers 0, 1, or 2 Use of qualitative terms (e.g. “acute”, “unilateral”, “severe”)
Appropriate narrowing of differential diagnosis 0, 1, or 2 Including key features to narrow the differential diagnosis
Transformation of information 0, 1, or 2 Use of medical terminology (e.g. “Fever” instead of Temperature: 39.4 °C”
Factual accuracy 0 (No), 1(Yes) Only accurate information included
Patient name 0 (No), 1 (Yes) The (virtual) patient is addressed by name and not called “the patient”.
Global rating 0, 1, or 2 Overall rating
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