Multi-field-of-view framework for distinguishing tumor grade in ER+ breast cancer from entire histopathology slides    建议了预测评分模型，并比较不同模型的优劣。

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Dermatologist-level classification of skin cancer with deep neural networks. Nature 

Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study. Lancet （多中心、数量庞大，病种多，算法多）

Computerized nuclear morphometric features from H&E slide images are prognostic of recurrence and predictive of added benefit of adjuvant chemotherapy in early stage non-small cell lung cancer. Presented at the United States and Canadian Academy of Pathology’s 108th Annual Meeting. 

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High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: application to invasive breast cancer detection. PLOS ONE 13, e0196828 (2018). 

. Deep learning based tissue analysis predicts outcome in colorectal cancer. Sci. Rep

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