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Deep Learning Provides Rapid Screen for Breast Cancer Metastasis with Sentinel Lymph Nodes

Autor: Allam, Kareem, Wang, Xiaohong Iris, Zhang, Songlin, Ding, Jianmin, Chiu, Kevin, Saluja, Karan, Wahed, Amer, Sun, Hongxia, Nguyen, Andy N. D.

Deep learning has been shown to be useful to detect breast cancer metastases by analyzing whole slide images of sentinel lymph nodes. However, it requires extensive scanning and analysis of all the lymph nodes slides for each case. Our deep learning

Externí odkaz: http://arxiv.org/abs/2301.05938

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Automated Diagnosis of Lymphoma with Digital Pathology Images Using Deep Learning

Autor: Achi, Hanadi El, Belousova, Tatiana, Chen, Lei, Wahed, Amer, Wang, Iris, Hu, Zhihong, Kanaan, Zeyad, Rios, Adan, Nguyen, Andy N. D.

Recent studies have shown promising results in using Deep Learning to detect malignancy in whole slide imaging. However, they were limited to just predicting positive or negative finding for a specific neoplasm. We attempted to use Deep Learning with

Externí odkaz: http://arxiv.org/abs/1811.02668

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Proteomics Analysis of FLT3-ITD Mutation in Acute Myeloid Leukemia Using Deep Learning Neural Network

Autor: Liang, Christine A., Chen, Lei, Wahed, Amer, Nguyen, Andy N. D.

Deep Learning can significantly benefit cancer proteomics and genomics. In this study, we attempt to determine a set of critical proteins that are associated with the FLT3-ITD mutation in newly-diagnosed acute myeloid leukemia patients. A Deep Learni

Externí odkaz: http://arxiv.org/abs/1801.01019

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