PMC-LLaMA: toward building open-source language models for medicine

C Wu, W Lin, X Zhang, Y Zhang, W Xie… - Journal of the …, 2024 - academic.oup.com
Objective Recently, large language models (LLMs) have showcased remarkable capabilities
in natural language understanding. While demonstrating proficiency in everyday …

Medalign: A clinician-generated dataset for instruction following with electronic medical records

SL Fleming, A Lozano, WJ Haberkorn… - Proceedings of the …, 2024 - ojs.aaai.org
The ability of large language models (LLMs) to follow natural language instructions with
human-level fluency suggests many opportunities in healthcare to reduce administrative …

Comparative evaluation of LLMs in clinical oncology

NR Rydzewski, D Dinakaran, SG Zhao, E Ruppin… - Nejm Ai, 2024 - ai.nejm.org
Background As artificial intelligence (AI) tools become widely accessible, more patients and
medical professionals will turn to them for medical information. Large language models …

Bimedix: Bilingual medical mixture of experts llm

S Pieri, SS Mullappilly, FS Khan, RM Anwer… - arXiv preprint arXiv …, 2024 - arxiv.org
In this paper, we introduce BiMediX, the first bilingual medical mixture of experts LLM
designed for seamless interaction in both English and Arabic. Our model facilitates a wide …

Towards safe large language models for medicine

T Han, A Kumar, C Agarwal… - ICML 2024 Workshop on …, 2024 - openreview.net
As large language models (LLMs) develop ever-improving capabilities and are applied in
real-world settings, it is important to understand their safety. While initial steps have been …

Towards safe and aligned large language models for medicine

T Han, A Kumar, C Agarwal, H Lakkaraju - arXiv preprint arXiv:2403.03744, 2024 - arxiv.org
The capabilities of large language models (LLMs) have been progressing at a breathtaking
speed, leaving even their own developers grappling with the depth of their potential and …

IryoNLP at MEDIQA-CORR 2024: Tackling the Medical Error Detection & Correction Task On the Shoulders of Medical Agents

JP Corbeil - arXiv preprint arXiv:2404.15488, 2024 - arxiv.org
In natural language processing applied to the clinical domain, utilizing large language
models has emerged as a promising avenue for error detection and correction on clinical …

HSE NLP Team at MEDIQA-CORR 2024 Task: In-Prompt Ensemble with Entities and Knowledge Graph for Medical Error Correction

A Valiev, E Tutubalina - Proceedings of the 6th Clinical Natural …, 2024 - aclanthology.org
This paper presents our LLM-based system designed for the MEDIQA-CORR@ NAACL-
ClinicalNLP 2024 Shared Task 3, focusing on medical error detection and correction in …

PretextTrans: Investigating Medical Factual Knowledge Mastery of LLMs with Predicate-text Dual Transformation

Y Zhou, X Liu, C Ning, J Wu - arXiv preprint arXiv:2409.14302, 2024 - arxiv.org
In the study, we aim to investigate current LLMs' mastery of medical factual knowledge with a
dynamic evaluation schema, which can automatically generate multiple test samples for …

Zero‐and few‐shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials

S Šuster, T Baldwin, K Verspoor - Research Synthesis Methods - Wiley Online Library
Existing systems for automating the assessment of risk‐of‐bias (RoB) in medical studies are
supervised approaches that require substantial training data to work well. However, recent …