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Plos One|May 13, 2020
Using case-level context to classify cancer pathology reportsShang Gao, Mohammed Alawad, Noah Schaefferkoetter, et al.
Journal of the American Medical Informatics Association : JAMIA|November 12, 2019
Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networksMohammed Alawad, Shang Gao, John X Qiu, et al.
IEEE Journal of Biomedical and Health Informatics|February 26, 2021
Limitations of Transformers on Clinical Text ClassificationShang Gao, Mohammed Alawad, M Todd Young, et al.
BMC Bioinformatics|March 22, 2021
Deep active learning for classifying cancer pathology reportsKevin De Angeli, Shang Gao, Mohammed Alawad, et al.
IEEE Transactions on Emerging Topics in Computing|September 19, 2022
Privacy-Preserving Deep Learning NLP Models for Cancer RegistriesMohammed Alawad, Hong-Jun Yoon, Shang Gao, et al.
JAMIA Open|September 16, 2022
Using ensembles and distillation to optimize the deployment of deep learning models for the classification of electronic cancer pathology reportsKevin De Angeli, Shang Gao, Andrew Blanchard, et al.
... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics|September 9, 2022
Deep Transfer Learning Across Cancer Registries for Information Extraction from Pathology ReportsMohammed Alawad, Shang Gao, John Qiu, et al.
Artificial Intelligence in Medicine|December 10, 2019
Classifying cancer pathology reports with hierarchical self-attention networksShang Gao, John X Qiu, Mohammed Alawad, et al.
Frontiers in Oncology|October 22, 2019
AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance ComputingTanmoy Bhattacharya, Thomas Brettin, James H Doroshow, et al.
Medical Physics|August 23, 2024
The United States Department of Energy and National Institutes of Health Collaboration: Medical Care Advances by Discovery in Radiation DetectionJeffrey Buchsbaum, Jacek Capala, Ceferino Obcemea, et al.
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