
Send us Fan Mail What happens when AI models that perform almost perfectly on scattered cervical cells become less reliable than a coin flip on crowded cell groups? In DigiPath Digest #51, I examine what this performance gap tells us about artificial intelligence in cytopathology. The first paper evaluated six convolutional neural network models trained to distinguish benign from high-grade lesions using scattered cervical cytology cells. The models achieved AUCs ranging from 0.950 to 0.996 o...
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250: AI for Scientific Writing: 4 Rules from a Pathologist

242: Are Foundation Models Really Better for Digital Pathology? Podcast with Panu Kauppila

241: Screening Efficiency Over Experience: Rethinking Cytology Expertise

240: Computational Pathology Is Changing Companion Diagnostics
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