most citedM3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.IR20262 cited

M3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

Rafi Al Attrach, Pedro Moreira, Rajna Fani +3

Large-scale clinical databases offer opportunities for medical research, but their complexity creates barriers to effective use. The Medical Information Mart for Intensive Care (MI…

cs.DL2025

The Power of Data Communities

Lucas McCullum, Miguel Angel Armengol de la Hoz, Catherine Bielick +10

Datasets together with active scientific communities prepared to leverage them can contribute to scientific progress and facilitate making research more equitable. In this study we…

cs.DL2025

The Community Index: A More Comprehensive Approach to Assessing Scholarly Impact

Arav Kumar, Cameron Sabet, Alessandro Hammond +9

The h index is a widely recognized metric for assessing the research impact of scholars, defined as the maximum value h such that the scholar has published h papers each cited at l…

cs.LG2025

An Algorithmic Approach for Causal Health Equity: A Look at Race Differentials in Intensive Care Unit (ICU) Outcomes

Drago Plecko, Paul Secombe, Andrea Clarke +7

The new era of large-scale data collection and analysis presents an opportunity for diagnosing and understanding the causes of health inequities. In this study, we describe a frame…

cs.CL2024

Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias

Shan Chen, Jack Gallifant, Mingye Gao +12

Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in t…