Resources

This dataset was designed and created to enable advancements in healthcare-focused large language models, particularly in the context of retrieval-augmented clinical question-answering capabilities. Developed using a self-constructed pipeline based …

Widespread disparities in clinical outcomes exist between different demographic groups in the United States. A new line of work in medical sociology has demonstrated physicians often use stigmatizing language in electronic medical records within cer…

The MIMIC-IV-ECG module contains approximately 800,000 diagnostic electrocardiograms across nearly 160,000 unique patients. These diagnostic ECGs use 12 leads and are 10 seconds in length. They are sampled at 500 Hz. This subset contains all of the …

We introduce a dataset of people’s names and clinical note templates to support research on the demographic bias of de-identification systems. The dataset contains 16 name sets that vary along four demographic dimensions: gender, race, name populari…

The Radiology Report Expert Evaluation (ReXVal) Dataset is a publicly available dataset of radiologist evaluations of errors in automatically generated radiology reports. The dataset contains annotations from 6 board certified radiologists on clinic…

The medical specialty of critical care, or intensive care, provides emergency medical care to patients suffering from life-threatening complications and injuries. The medical specialty is featured by the generation of a huge amount of high-granulari…

We present a radiology question answering dataset, RadQA, with 3074 questions posed against radiology reports and annotated with their corresponding answer spans (resulting in a total of 6148 question-answer evidence pairs) by physicians. The questi…

Reliable longitudinal risk prediction for hospitalized patients is needed to provide quality care. Our goal is to foster the development of generalizable models capable of leveraging clinical notes to predict healthcare-associated diseases 24–96 hou…

The MIMIC-IV-ECG Demo module contains 659 diagnostic electrocardiograms across 92 unique patients. These 92 patients overlap with the patients from the MIMIC-IV Clinical Demo and are also part of the MIMIC-IV Clinical Database. These diagnostic ECGs…

We created a dataset of clinical action items annotated over MIMIC-III. This dataset, which we call CLIP, is annotated by physicians and covers 718 discharge summaries, representing 107,494 sentences. Annotations were collected as character-level sp…