Resources

Generative vision-language models have exciting potential implications for radiology report generation, but unfortunately such models are also known to produce hallucinations and other nonsensical statements. For example, radiology report generation…

Preliminary datasets containing skin conductance recordings where experiments involve artificial stimuli are available online. However, recordings of a longer duration acquired during real-world cognitive stressors are lacking significantly. This da…

The MIMIC-IV-Echo module contains structured echocardiographic measurements and DICOM files from echocardiography exams. Structured measurements are available from 206,488 echocardiogram studies (including 179,928 transthoracic, 16,389 stress, and 1…

The Brazilian Multilabel Ophthalmological Dataset (BRSET) is a multi-labeled ophthalmological dataset designed to improve scientific community development and validate machine learning models. In ophthalmology, ancillary exams support medical decisi…

The ER-Reason dataset is a benchmark designed to evaluate LLM-based clinical reasoning and decision-making in the emergency room (ER), a high-stakes setting where clinicians make rapid, consequential decisions across diverse patient presentations an…

With the rapid development of generative LLMs (large language models) in the field of natural language processing, their potential in medical applications has become increasingly evident. However, most existing studies rely on exam-style questions o…

LLaVA-Rad MIMIC-CXR features more accurate section extractions from MIMIC-CXR free-text radiology reports. Traditionally, rule-based methods were used to extract sections such as the reason for exam, findings, and impression. However, these approach…

Clinical decision making is one of the most impactful parts of a physician's responsibilities and stands to benefit greatly from AI solutions such as large language models (LLMs). However, while many datasets exist to test the performance of AI mode…

Computational medicine research requires clinical data for training and testing purposes, so the development of datasets composed of real hospital data is of utmost importance in this field. Most such data collections are in the English language, we…

Breast cancer is one of the most prevalent types of cancer and the leading type of cancer death. Mammography is the recommended imaging modality for periodic breast cancer screening. A few datasets have been published to develop computer-aided tools…