146 citations · 234 across the 6 of their papers we have counts for
6 papers
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
Zheng Yu, Yikuan Li, Joseph Kim +3
Dynamic diagnosis is desirable when medical tests are costly or time-consuming. In this work, we use reinforcement learning (RL) to find a dynamic policy that selects lab test pane…
Using Machine Learning to Develop Smart Reflex Testing Protocols
Matthew McDermott, Anand Dighe, Peter Szolovits +2
Objective: Reflex testing protocols allow clinical laboratories to perform second line diagnostic tests on existing specimens based on the results of initially ordered tests. Refle…
A Comparative Study of Pretrained Language Models for Long Clinical Text
Yikuan Li, Ramsey M. Wehbe, Faraz S. Ahmad +2
Objective: Clinical knowledge enriched transformer models (e.g., ClinicalBERT) have state-of-the-art results on clinical NLP (natural language processing) tasks. One of the core li…
Multimodal Machine Learning in Precision Health
Adrienne Kline, Hanyin Wang, Yikuan Li +6
As machine learning and artificial intelligence are more frequently being leveraged to tackle problems in the health sector, there has been increased interest in utilizing them in…
Machine Learning Applications in Lung Cancer Diagnosis, Treatment and Prognosis
Yawei Li, Xin Wu, Ping Yang +2
The recent development of imaging and sequencing technologies enables systematic advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in effectively…
Clinical-Longformer and Clinical-BigBird: Transformers for long clinical sequences
Yikuan Li, Ramsey M. Wehbe, Faraz S. Ahmad +2
Transformers-based models, such as BERT, have dramatically improved the performance for various natural language processing tasks. The clinical knowledge enriched model, namely Cli…