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Found 7 papers, 1 papers with code
A Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare
It has gained significant attention in the field of Natural Language Processing (NLP) due to its ability to learn optimal strategies for tasks such as dialogue systems, machine translation, and question-answering.
Fault Separation Based on An Excitation Operator with Application to a Quadrotor UAV
This paper presents an excitation operator based fault separation architecture for a quadrotor unmanned aerial vehicle (UAV) subject to loss of effectiveness (LoE) faults, actuator aging, and load uncertainty.
An In-Depth Evaluation of Federated Learning on Biomedical Natural Language Processing
Language models (LMs) such as BERT and GPT have revolutionized natural language processing (NLP).
A Cross-institutional Evaluation on Breast Cancer Phenotyping NLP Algorithms on Electronic Health Records
We developed three types of NLP models (i. e., conditional random field, bi-directional long short-term memory and CancerBERT) to extract cancer phenotypes from clinical texts.
Predicting Cancer Treatments Induced Cardiotoxicity of Breast Cancer Patients
After adjusting for baseline differences in cardiovascular health, patients who received chemotherapy or targeted therapy appeared to have higher risk of cardiotoxicity than patients who received radiation therapy.
CancerBERT: a BERT model for Extracting Breast Cancer Phenotypes from Electronic Health Records
This data used in the study included 21, 291 breast cancer patients diagnosed from 2010 to 2020, patients' clinical notes and pathology reports were collected from the University of Minnesota Clinical Data Repository (UMN).
Deep Learning Approaches for Extracting Adverse Events and Indications of Dietary Supplements from Clinical Text
The best performed NER and RE models were further applied on clinical notes mentioning 88 DS for discovering DS adverse events and indications, which were compared with a DS knowledge base.
