210 citations · 244 across the 5 of their papers we have counts for
6 papers
Bias Detection in Emergency Psychiatry: Linking Negative Language to Diagnostic Disparities
Alissa A. Valentine, Lauren A. Lepow, Donald Apakama +3
The emergency department (ED) is a high stress environment with increased risk of clinician bias exposure. In the United States, Black patients are more likely than other racial/et…
Fair Machine Learning for Healthcare Requires Recognizing the Intersectionality of Sociodemographic Factors, a Case Study
Alissa A. Valentine, Alexander W. Charney, Isotta Landi
As interest in implementing artificial intelligence (AI) in medical systems grows, discussion continues on how to evaluate the fairness of these systems, or the disparities they ma…
The Point of View of a Sentiment: Towards Clinician Bias Detection in Psychiatric Notes
Alissa A. Valentine, Lauren A. Lepow, Lili Chan +2
Negative patient descriptions and stigmatizing language can contribute to generating healthcare disparities in two ways: (1) read by patients, they can harm their trust and engagem…
Extracting Social Support and Social Isolation Information from Clinical Psychiatry Notes: Comparing a Rule-based NLP System and a Large Language Model
Braja Gopal Patra, Lauren A. Lepow, Praneet Kasi Reddy Jagadeesh Kumar +16
Background: Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), indivi…
Clinical Text Deduplication Practices for Efficient Pretraining and Improved Clinical Tasks
Isotta Landi, Eugenia Alleva, Alissa A. Valentine +2
Despite being a unique source of information on patients' status and disease progression, clinical notes are characterized by high levels of duplication and information redundancy.…
Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale
Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee +6
Deriving disease subtypes from electronic health records (EHRs) can guide next-generation personalized medicine. However, challenges in summarizing and representing patient data pr…