Resources


Database Open Access

MIMIC-IV Clinical Database Demo on FHIR

Alex Bennett, Joshua Wiedekopf, Hannes Ulrich, Alistair Johnson

MIMIC-IV-on-FHIR is a hundred patient demo of MIMIC-IV v2.0 in the Fast Healthcare Interoperability Resources(FHIR) format. MIMIC-IV-on-FHIR provides implementers with a real-world FHIR datastore to aid in FHIR research and development.

fhir electronic health records mimic

Published: June 7, 2022. Version: 2.0

Database Credentialed Access

MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Harshita Sharma, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez Valle, Hoifung Poon, Ozan Oktay

MS-CXR is a new dataset containing 1162 chest X-ray bounding box labels paired with radiology text descriptions, annotated and verified by two board-certified radiologists.

vision-language processing localization phrase grounding chest x-ray

Published: Nov. 15, 2024. Version: 1.1.0

Database Credentialed Access

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

Shruthi Bannur, Stephanie Hyland, Qianchu Liu, Fernando Pérez-García, Max Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anton Schwaighofer, Maria Teodora Wetscherek, Hannah Richardson, Tristan Naumann, Javier Alvarez Valle, Ozan Oktay

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.

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

Published: March 17, 2023. Version: 1.0.0

Model Credentialed Access

Medical AI Research Foundations: A repository of medical foundation models

Shekoofeh Azizi, Jan Freyberg, Laura Culp, Patricia MacWilliams, Sara Mahdavi, Vivek Natarajan, Alan Karthikesalingam

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

Published: April 25, 2023. Version: 1.0.0

Database Credentialed Access

MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We introduce MIMIC-Ext-MIMIC-CXR-VQA, a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs.

question answering multimodal benchmark radiology evaluation visual question answering electronic health records deep learning machine learning chest x-ray

Published: July 19, 2024. Version: 1.0.0

Database Credentialed Access

MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We introduce MIMIC-Ext-MIMIC-CXR-VQA, a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs.

question answering multimodal benchmark radiology evaluation visual question answering electronic health records deep learning machine learning chest x-ray

Published: July 19, 2024. Version: 1.0.0

Database Credentialed Access

RuMedNLI: A Russian Natural Language Inference Dataset For The Clinical Domain

Pavel Blinov, Aleksandr Nesterov, Galina Zubkova, Arina Reshetnikova, Vladimir Kokh, Chaitanya Shivade

RuMedNLI is the full counterpart dataset of MedNLI in Russian language.

natural language inference recognizing textual entailment russian language

Published: April 1, 2022. Version: 1.0.0

Database Open Access

NInFEA: Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research

Danilo Pani, Eleonora Sulas, Monica Urru, Reza Sameni, Luigi Raffo, Roberto Tumbarello

Open dataset featuring non-invasive electrophysiological recordings, fetal pulsed-wave Doppler and maternal respiration signals. It provides a ground truth on the fetal heart activity when an invasive scalp lead is unavailable.

foetus pwd doppler foetal ecg maternal ecg pwd envelope non-invasive cardiology early pregnancy antenatal fecg ecg

Published: Nov. 12, 2020. Version: 1.0.0

Visualize waveforms

Model Credentialed Access

Me-LLaMA: Foundation Large Language Models for Medical Applications

Qianqian Xie, Qingyu Chen, Aokun Chen, Cheng Peng, Yan Hu, Fongci Lin, Xueqing Peng, Jimin Huang, Jeffrey Zhang, Vipina Keloth, Xinyu Zhou, Huan He, Lucila Ohno-Machado, Yonghui Wu, Hua Xu, Jiang Bian

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

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, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

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

Published: July 23, 2024. Version: 1.0.0