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README.md
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We trained HistoGPT on a large-scale dataset of 6,000 patient-report pairs from over 12,000 whole slide images (WSIs) of over 150 different skin conditions (healthy, inflammatory, cancerous, ...) provided by the Department of Dermatology at the Technical University of Munich (TUM). To test our model, we extensively evaluated HistoGPT on five external cohorts from five different countries, including a dataset of 1,300 patient-report pairs from the Department of Dermatology at the University Hospital Münster (UKM).
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The full code of our project is available on [GitHub](https://huggingface.co/marr-peng-lab/histogpt)
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We trained HistoGPT on a large-scale dataset of 6,000 patient-report pairs from over 12,000 whole slide images (WSIs) of over 150 different skin conditions (healthy, inflammatory, cancerous, ...) provided by the Department of Dermatology at the Technical University of Munich (TUM). To test our model, we extensively evaluated HistoGPT on five external cohorts from five different countries, including a dataset of 1,300 patient-report pairs from the Department of Dermatology at the University Hospital Münster (UKM).
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The full code of our project is available on [GitHub](https://huggingface.co/marr-peng-lab/histogpt). At the moment only the model weights are hosted here on Hugging Face.
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