FedNER: Medical Named Entity Recognition with Federated Learning

By Suyu Ge, Fangzhao Wu, Chuhan Wu, Tao Qi, Yongfeng Huang, Xing Xie. 2020

23 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Chaoyang He
2. Yang Liu
3. Murali Annavaram
4. Qiang Yang
5. Jinhyun So
6. Abhishek Singh
7. Praneeth Vepakomma
8. Qinbin Li

Citations in the corpus

• FedML: A Research Library and Benchmark for Federated Machine Learning (2020, background): “Promising application domains include, but are not limited to, computer vision [77, 78], natural language processing [79, 80, 81, 82, 83], finance [74, 35, 84], transportation [85, 86, 87, 88, 89, 90, 91, 92, 93, 94], digital health [95, 96, 97, 98, 99, 100, 101], recommendation [102, 103, 104, 105,…”
• Communication-efficient federated learning via knowledge distillation (2021, unknown): “, 2019) and medical natural language processing (Ge et al., 2020).”