Cover Image

Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rahman, Salman, Jiang, Lavender Yao, Gabriel, Saadia, Aphinyanaphongs, Yindalon, Oermann, Eric Karl, Chunara, Rumi
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Computers and Society Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generalist Large Language Models Outperform Clinical Tools on Medical Benchmarks
by: Vishwanath, Krithik, et al.
Published: (2025)

Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke
by: Kapoor, Anjali K., et al.
Published: (2026)

Paradox of De-identification: A Critique of HIPAA Safe Harbour in the Age of LLMs
by: Jiang, Lavender Y., et al.
Published: (2026)

Impact on Public Health Decision Making by Utilizing Big Data Without Domain Knowledge
by: Zhang, Miao, et al.
Published: (2024)

Refining Packing and Shuffling Strategies for Enhanced Performance in Generative Language Models
by: Chen, Yanbing, et al.
Published: (2024)

Understanding Disparities in Post Hoc Machine Learning Explanation
by: Mhasawade, Vishwali, et al.
Published: (2024)

BPQA Dataset: Evaluating How Well Language Models Leverage Blood Pressures to Answer Biomedical Questions
by: Hang, Chi, et al.
Published: (2025)

Disparate Effect Of Missing Mediators On Transportability of Causal Effects
by: Mhasawade, Vishwali, et al.
Published: (2024)

Identity-Robust Language Model Generation via Content Integrity Preservation
by: Zhang, Miao, et al.
Published: (2026)

AI Safety in Generative AI Large Language Models: A Survey
by: Chua, Jaymari, et al.
Published: (2024)

It is Too Many Options: Pitfalls of Multiple-Choice Questions in Generative AI and Medical Education
by: Singh, Shrutika, et al.
Published: (2025)

Generalist Foundation Models Are Not Clinical Enough for Hospital Operations
by: Jiang, Lavender Y., et al.
Published: (2025)

The World of Generative AI: Deepfakes and Large Language Models
by: Mitra, Alakananda, et al.
Published: (2024)

Speciesism in AI: Evaluating Discrimination Against Animals in Large Language Models
by: Jotautaitė, Monika, et al.
Published: (2025)

Dual Use Concerns of Generative AI and Large Language Models
by: Grinbaum, Alexei, et al.
Published: (2023)

Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration
by: Ding, Kexin, et al.
Published: (2025)

Will Large Language Models Transform Clinical Prediction?
by: Yildiz, Yusuf, et al.
Published: (2025)

AGGA: A Dataset of Academic Guidelines for Generative AI and Large Language Models
by: Jiao, Junfeng, et al.
Published: (2025)

Large Language Models and Forensic Linguistics: Navigating Opportunities and Threats in the Age of Generative AI
by: Mikros, George
Published: (2025)

A Comprehensive Survey on the Trustworthiness of Large Language Models in Healthcare
by: Aljohani, Manar, et al.
Published: (2025)

MalAlgoQA: Pedagogical Evaluation of Counterfactual Reasoning in Large Language Models and Implications for AI in Education
by: Liu, Naiming, et al.
Published: (2024)

Evaluating Proactive Risk Awareness of Large Language Models
by: Luo, Xuan, et al.
Published: (2026)

Extrinsic Evaluation of Cultural Competence in Large Language Models
by: Bhatt, Shaily, et al.
Published: (2024)

Configurable Fairness: Direct Optimization of Parity Metrics via Vision-Language Models
by: Zhang, Miao, et al.
Published: (2024)

Bias and Volatility: A Statistical Framework for Evaluating Large Language Model's Stereotypes and the Associated Generation Inconsistency
by: Liu, Yiran, et al.
Published: (2024)

Evaluating Digital Inclusiveness of Digital Agri-Food Tools Using Large Language Models: A Comparative Analysis Between Human and AI-Based Evaluations
by: Pewinya, Githma, et al.
Published: (2026)

New-Onset Diabetes Assessment Using Artificial Intelligence-Enhanced Electrocardiography
by: Zhang, Hao, et al.
Published: (2022)

Evaluating open-source Large Language Models for automated fact-checking
by: Fontana, Nicolo', et al.
Published: (2025)

Towards Equitable AI: Detecting Bias in Using Large Language Models for Marketing
by: Yilmaz, Berk, et al.
Published: (2025)

Human-Level and Beyond: Benchmarking Large Language Models Against Clinical Pharmacists in Prescription Review
by: Yang, Yan, et al.
Published: (2025)

Understanding Teacher Revisions of Large Language Model-Generated Feedback
by: Borchers, Conrad, et al.
Published: (2026)

Regulating Large Language Models: A Roundtable Report
by: Nicholas, Gabriel, et al.
Published: (2024)

Can AI Relate: Testing Large Language Model Response for Mental Health Support
by: Gabriel, Saadia, et al.
Published: (2024)

What do Large Language Models Say About Animals? Investigating Risks of Animal Harm in Generated Text
by: Kanepajs, Arturs, et al.
Published: (2025)

Evaluation of AI Ethics Tools in Language Models: A Developers' Perspective Case Study
by: Silva, Jhessica, et al.
Published: (2025)

Cancer-Myth: Evaluating Large Language Models on Patient Questions with False Presuppositions
by: Zhu, Wang Bill, et al.
Published: (2025)

Not All Jokes Land: Evaluating Large Language Models Understanding of Workplace Humor
by: Shafiei, Mohammadamin, et al.
Published: (2025)

Leveraging Large Language Models for Actionable Course Evaluation Student Feedback to Lecturers
by: Zhang, Mike, et al.
Published: (2024)

Topic-aware Large Language Models for Summarizing the Lived Healthcare Experiences Described in Health Stories
by: Bilalpur, Maneesh, et al.
Published: (2025)

Smart Trial: Evaluating the Use of Large Language Models for Recruiting Clinical Trial Participants via Social Media
by: Zhou, Xiaofan, et al.
Published: (2025)