most citedEthical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice

2 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL20241 cited

A Benchmark for Long-Form Medical Question Answering

Pedram Hosseini, Jessica M. Sin, Bing Ren +4

There is a lack of benchmarks for evaluating large language models (LLMs) in long-form medical question answering (QA). Most existing medical QA evaluation benchmarks focus on auto…

cs.CY20242 cited

Ethical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice

Ellison B. Weiner, Irene Dankwa-Mullan, William A. Nelson +1

Artificial intelligence (AI) has rapidly transformed various sectors, including healthcare, where it holds the potential to revolutionize clinical practice and improve patient outc…

cs.CL2024

ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentence

Yuxin Wang, Xiaomeng Zhu, Weimin Lyu +2

Handling implicit language is essential for natural language processing systems to achieve precise text understanding and facilitate natural interactions with users. Despite its im…

cs.CV2024

Prediction of Breast Cancer Recurrence Risk Using a Multi-Model Approach Integrating Whole Slide Imaging and Clinicopathologic Features

Manu Goyal, Jonathan D. Marotti, Adrienne A. Workman +6

Breast cancer is the most common malignancy affecting women worldwide and is notable for its morphologic and biologic diversity, with varying risks of recurrence following treatmen…

cs.CV2023

Improving Representation Learning for Histopathologic Images with Cluster Constraints

Weiyi Wu, Chongyang Gao, Joseph DiPalma +2

Recent advances in whole-slide image (WSI) scanners and computational capabilities have significantly propelled the application of artificial intelligence in histopathology slide a…

cs.CL2023

Proto-lm: A Prototypical Network-Based Framework for Built-in Interpretability in Large Language Models

Sean Xie, Soroush Vosoughi, Saeed Hassanpour

Large Language Models (LLMs) have significantly advanced the field of Natural Language Processing (NLP), but their lack of interpretability has been a major concern. Current method…