24 citations · 37 across the 7 of their papers we have counts for
9 papers
Multi-Task Training with In-Domain Language Models for Diagnostic Reasoning
Brihat Sharma, Yanjun Gao, Timothy Miller +3
Generative artificial intelligence (AI) is a promising direction for augmenting clinical diagnostic decision support and reducing diagnostic errors, a leading contributor to medica…
Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes
Yanjun Gao, Dmitriy Dligach, Timothy Miller +2
The BioNLP Workshop 2023 initiated the launch of a shared task on Problem List Summarization (ProbSum) in January 2023. The aim of this shared task is to attract future research ef…
Progress Note Understanding -- Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 Shared Task
Yanjun Gao, Dmitriy Dligach, Timothy Miller +3
Daily progress notes are common types in the electronic health record (EHR) where healthcare providers document the patient's daily progress and treatment plans. The EHR is designe…
DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing
Yanjun Gao, Dmitriy Dligach, Timothy Miller +4
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priori…
Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding
Yanjun Gao, Dmitriy Dligach, Timothy Miller +4
Applying methods in natural language processing on electronic health records (EHR) data is a growing field. Existing corpus and annotation focus on modeling textual features and re…
A Scoping Review of Publicly Available Language Tasks in Clinical Natural Language Processing
Yanjun Gao, Dmitriy Dligach, Leslie Christensen +7
Objective: to provide a scoping review of papers on clinical natural language processing (NLP) tasks that use publicly available electronic health record data from a cohort of pati…
Classifying Long Clinical Documents with Pre-trained Transformers
Xin Su, Timothy Miller, Xiyu Ding +2
Automatic phenotyping is a task of identifying cohorts of patients that match a predefined set of criteria. Phenotyping typically involves classifying long clinical documents that…
Two-stage Federated Phenotyping and Patient Representation Learning
Dianbo Liu, Dmitriy Dligach, Timothy Miller
A large percentage of medical information is in unstructured text format in electronic medical record systems. Manual extraction of information from clinical notes is extremely tim…
Learning Patient Representations from Text
Dmitriy Dligach, Timothy Miller
Mining electronic health records for patients who satisfy a set of predefined criteria is known in medical informatics as phenotyping. Phenotyping has numerous applications such as…