Area of research
Artificial Intelligence · Molecular Biology
Research interest
Research interests include Computer science, Medicine, Health records, Natural language processing, Speech recognition, and Speaker recognition.
Douchi-derived Bacillus subtilis modulates gut microbiota and bile acid metabolism to alleviate metformin-induced diarrhea in type 2 diabetes mellitus
Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias
Design and development of a machine-learning-driven opioid overdose risk prediction tool integrated in electronic health records in primary care settings
Early prediction of Alzheimer's disease and related dementias using real‐world electronic health records
Enriching Real-world Data with Social Determinants of Health for Health Outcomes and Health Equity: Successes, Challenges, and Opportunities
Noninvasive Diagnosis of Nonalcoholic Steatohepatitis and Advanced Liver Fibrosis Using Machine Learning Methods: Comparative Study With Existing Quantitative Risk Scores
Extracting social determinants of health from electronic health records using natural language processing: a systematic review
Transformer-based named entity recognition for parsing clinical trial eligibility criteria
Identification of important factors in an inpatient fall risk prediction model to improve the quality of care using EHR and electronic administrative data: A machine-learning approach
Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions
Disentangling Correlated Speaker and Noise for Speech Synthesis via Data Augmentation and Adversarial Factorization
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
Neural Information Processing Systems 2018cited by 230position: last
A study of generalizability of recurrent neural network-based predictive models for heart failure onset risk using a large and heterogeneous EHR data set
Extraction of BI-RADS findings from breast ultrasound reports in Chinese using deep learning approaches
Computable Eligibility Criteria through Ontology-driven Data Access: A Case Study of Hepatitis C Virus Trials.
PubMed 2018cited by 18position: middle
A long journey to short abbreviations: developing an open-source framework for clinical abbreviation recognition and disambiguation (CARD)
A comparison of conditional random fields and structured support vector machines for chemical entity recognition in biomedical literature