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 …

Both medical care and observational studies in oncology require a thorough understanding of a patient's disease progression and treatment history, often elaborately documented within clinical notes. As large language models (LLMs) are becoming more …

This study integrates the MIMIC-III and CORAL electronic health records into knowledge graphs to enhance their utility for advanced medical analysis and decision-making. MIMIC-III contains comprehensive data from over 40,000 patients, while CORAL fo…

Deep learning technologies have been widely adopted in medical imaging due to their ability to extract features from images and make accurate diagnoses automatically. Medical imaging technologies are particularly useful because they can be trained t…

This project focuses on Task 2 of the 2014 ShARe/CLEF eHealth evaluation lab, which extended Task 1 of the 2013 ShARe/CLEF eHealth evaluation lab by focusing on identification and normalization of disorder attributes. The task comprises two subtasks…

This is the pilot year of the ShARe/CLEF eHealth Evaluation Lab, a shared task focused on natural language processing (NLP) and information retrieval (IR) for clinical care. The task is co-organized by the Shared Annotated Resources (ShARe) project …

Immunosuppression due to underlying conditions or immunosuppressive medication use increases the risk of morbidity and mortality in the context of infectious disease. Identifying patients with immunosuppression is important for better studying and u…

Visual Question Answering (VQA) enables flexible and context-dependent analysis of medical images, such as chest X-rays (CXRs), by allowing users to pose specific questions and receive nuanced answers. However, existing CXR VQA datasets are typicall…

Radiology reports are essential for clinical care but pose challenges for automated processing due to their unstructured nature. Existing datasets like RadGraph-1.0 focus narrowly on chest X-rays (CXR), limiting their applicability. We introduce Rad…

The National Institutes of Health Stroke Scale (NIHSS) is a 15-item neurologic examination stroke scale. It quantifies the physical manifestations of neurological deficits and provides crucial support for clinical decision making and early-stage eme…