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Found 6 papers, 0 papers with code
IBMResearch at MEDIQA 2021: Toward Improving Factual Correctness of Radiology Report Abstractive Summarization
In our system, we first used a transformer-based encoder-decoder model to generate top N candidate impression summaries for a report, then trained another transformer-based model to predict a 14-observations-vector of the impression based on the findings and background of the report, and finally, utilized this vector to re-rank the candidate summaries.
Extracting Medication Changes in Clinical Narratives using Pre-trained Language Models
An accurate and detailed account of patient medications, including medication changes within the patient timeline, is essential for healthcare providers to provide appropriate patient care.
Toward Understanding Clinical Context of Medication Change Events in Clinical Narratives
Understanding medication events in clinical narratives is essential to achieving a complete picture of a patient's medication history.
WNTRAC: AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19
We present the Worldwide Non-pharmaceutical Interventions Tracker for COVID-19 (WNTRAC), a comprehensive dataset consisting of over 6, 000 NPIs implemented worldwide since the start of the pandemic.
Extracting Daily Dosage from Medication Instructions in EHRs: An Automated Approach and Lessons Learned
Medication timelines have been shown to be effective in helping physicians visualize complex patient medication information.
A Novel System for Extractive Clinical Note Summarization using EHR Data
While much data within a patient{'}s electronic health record (EHR) is coded, crucial information concerning the patient{'}s care and management remain buried in unstructured clinical notes, making it difficult and time-consuming for physicians to review during their usual clinical workflow.
