Area of research
Molecular Biology · Artificial Intelligence
Research interest
Research interests include Biomedical Text Mining and Ontologies, Topic Modeling, Natural Language Processing Techniques, and Data-Driven Disease Surveillance.
Large language models in global health
International partnership for governing generative artificial intelligence models in medicine
Establishing a multidisciplinary initiative for interoperable electronic health record innovations at an academic medical center
Adaptation of an NLP system to a new healthcare environment to identify social determinants of health
Development of Electronic Health Record–Based Prediction Models for 30-Day Readmission Risk Among Patients Hospitalized for Acute Myocardial Infarction
Comparative Effectiveness of Carotid Endarterectomy vs Initial Medical Therapy in Patients With Asymptomatic Carotid Stenosis
Portable Automated Surveillance of Surgical Site Infections Using Natural Language Processing
Impact of Different Electronic Cohort Definitions to Identify Patients With Atrial Fibrillation From the Electronic Medical Record
Moonstone: a novel natural language processing system for inferring social risk from clinical narratives
Detecting Evidence of Intra-abdominal Surgical Site Infections from Radiology Reports Using Natural Language Processing.
PubMed 2019cited by 35position: middle
Determining Onset for Familial Breast and Colorectal Cancer from Family History Comments in the Electronic Health Record.
PubMed 2019cited by 27position: middle
Interactive NLP in Clinical Care: Identifying Incidental Findings in Radiology Reports
Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.
PubMed 2019cited by 25position: middle
Determination of Marital Status of Patients from Structured and Unstructured Electronic Healthcare Data.
PubMed 2019cited by 22position: middle
Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances
Road Map For Diffusion Of Innovation In Health Care
Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients
NLPReViz: an interactive tool for natural language processing on clinical text
Understanding patient satisfaction with received healthcare services: A natural language processing approach.
PubMed 2016cited by 46position: middle
Extracting a stroke phenotype risk factor from Veteran Health Administration clinical reports: an information content analysis
Normalizing acronyms and abbreviations to aid patient understanding of clinical texts: ShARe/CLEF eHealth Challenge 2013, Task 2
SemEval-2015 Task 14: Analysis of Clinical Text
BluLab: Temporal Information Extraction for the 2015 Clinical TempEval Challenge
SemEval-2014 Task 7: Analysis of Clinical Text
Evaluating the state of the art in disorder recognition and normalization of the clinical narrative
Overview of the ShARe/CLEF eHealth Evaluation Lab 2014
Evaluating the effects of machine pre-annotation and an interactive annotation interface on manual de-identification of clinical text
Cue-based assertion classification for Swedish clinical text—Developing a lexicon for pyConTextSwe
Using Twitter to Examine Smoking Behavior and Perceptions of Emerging Tobacco Products
Overview of the ShARe/CLEF eHealth Evaluation Lab 2013