ArticleJournal of imaging informatics in medicine2026
Beyond Accuracy: A MultiDimensional Framework for Evaluating Medical Image Classification Through Win vs. Lose Model Comparisons.
Article in Journal of imaging informatics in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
High-performing deep learning models such as ResNet, originally optimized for large-scale natural image datasets, often fail to generalize when applied directly to medical imaging tasks. This study investigates the limitations of "off-the-shelf" models in the context of skin lesion classification using the DermaMNIST dataset. Through a systematic evaluation of 35 architectural configurations across varying image resolutions and depths, the analysis reveals that mid-depth architectures (3-4 layers) and intermediate resolutions (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.