Resources


Database Credentialed Access

ReXPref-Prior: A MIMIC-CXR Preference Dataset for Reducing Hallucinated Prior Exams in Radiology Report Generation

Oishi Banerjee, Hong-Yu Zhou, Subathra Adithan, et al.

We propose ReXPref-Prior, an adapted version of MIMIC-CXR where GPT-4 has removed references to prior exams from both findings and impression sections of chest X-ray reports.

chest x-rays reinforcement learning hallucination

Published: Aug. 14, 2024. Version: 1.0.0

Database Credentialed Access

RadGraph2: Tracking Findings Over Time in Radiology Reports

Adam Dejl, Sameer Khanna, Patricia Therese Pile, et al.

RadGraph2 is a dataset of 800 chest radiology reports annotated using a fine-grained entity-relationship schema, which captures key findings as well as mentions of changes that occurred in comparison with the previous radiology studies.

chest x-rays relation extraction disease progression information extraction radiology reports named entity recognition

Published: Aug. 8, 2024. Version: 1.0.0

Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, et al.

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering machine learning electronic health records evaluation chest x-ray multi-modal question answering ehr question answering semantic parsing benchmark deep learning visual question answering

Published: July 23, 2024. Version: 1.0.0

Model Credentialed Access

Me-LLaMA: Foundation Large Language Models for Medical Applications

Qianqian Xie, Qingyu Chen, Aokun Chen, et al.

Me-LLaMA is a family of large language models for medical applications trained using clinical text with LLaMA2 models as the base. We release model weights for the foundation models as well as the chat-enhanced models.

large language models

Published: June 5, 2024. Version: 1.0.0

Model Credentialed Access

Asclepius-R : Clinical Large Language Model Built On MIMIC-III Discharge Summaries

Sunjun Kweon, Junu Kim, Jiyoun Kim, et al.

Asclepius: Publicly Available Clinical Large Language Models with Synthetic Clinical Notes Asclepius-R: A instruction-finetuned large language model with MIMIC-III clinical notes

clinical notes synthetic clinical notes synthetic notes asclepius open-source llm clinical llm large language model

Published: March 25, 2024. Version: 1.1.0

Software Open Access

Transformer-DeID: Deidentification of free-text clinical notes with transformers

Callandra Moore, Lucas Bulgarelli, Tom Pollard, et al.

Fine tune transformer-based neural networks to deidentify clinical text data.

deidentification neural networks transformers

Published: Nov. 2, 2023. Version: 1.0.0

Database Credentialed Access

ReFiSco: Report Fix and Score Dataset for Radiology Report Generation

Katherine Tian, Sina J Hartung, Andrew A Li, et al.

Preliminary human expert evaluation study on 60 MIMIC-CXR radiology reports

Published: Aug. 23, 2023. Version: 0.0

Model Credentialed Access

Medical AI Research Foundations: A repository of medical foundation models

Shekoofeh Azizi, Jan Freyberg, Laura Culp, et al.

Medical AI Research Foundations is a repository of medical foundation models.

Published: April 25, 2023. Version: 1.0.0

Database Credentialed Access

MS-CXR-T: Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Qianchu Liu, et al.

The MS-CXR-T is a multimodal benchmark that enhances the MIMIC-CXR v2 dataset by including expert-verified annotations. Its goal is to evaluate biomedical visual-language processing models in terms of temporal semantics extracted from image and text.

disease progression cxr vision-language processing chest x-ray radiology multimodal

Published: March 17, 2023. Version: 1.0.0

Model Credentialed Access

Clinical-T5: Large Language Models Built Using MIMIC Clinical Text

Eric Lehman, Alistair Johnson

We train a T5-Base and T5-Large from scratch on MIMIC-III and MIMIC-IV. Additionally, we further pretrain T5-Base and SciFive on notes from MIMIC. We release these model weights on PhysioNet.

Published: Jan. 25, 2023. Version: 1.0.0