CCS Explorer: Relevance Prediction, Extractive Summarization, and Named Entity Recognition from Clinical Cohort Studies

Author:

Al-Hussaini Irfan1,Nakajima An Davi2,Lee Albert J.3,Bi Sarah4,Mitchell Cassie S.5

Affiliation:

1. Georgia Institute of Technology,Electrical and Computer Engineering,Atlanta,GA,USA

2. Georgia Institute of Technology,Computer Science,Atlanta,GA,USA

3. Georgia Institute of Technology,Machine Learning,Atlanta,GA,USA

4. Georgia Institute of Technology,Biomedical Engineering,Atlanta,GA,USA

5. Georgia Institute of Technology and Emory University,Biomedical Engineering and Machine Learning,Atlanta,GA,USA

Funder

National Science Foundation

Health

Georgia Institute of Technology

Emory University

Publisher

IEEE

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Advancing Clinical Text Summarization through Extractive Methods using BERT-Based Models on the NBME Dataset;2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS);2023-12-11

2. Data extraction methods for systematic review (semi)automation: Update of a living systematic review;F1000Research;2023-10-09

3. Literature-Based Discovery to Elucidate the Biological Links between Resistant Hypertension and COVID-19;Biology;2023-09-21

4. BioSift: A Dataset for Filtering Biomedical Abstracts for Drug Repurposing and Clinical Meta-Analysis;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

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