Resources

Large language models (LLMs) have shown impressive capabilities in solving a wide range of tasks based on human instructions. However, developing a conversational AI assistant for electronic health record (EHR) data remains challenging due to the la…

Interoperability of healthcare data has become increasingly important given the increase in deployment of data driven algorithms in clinical settings. The Fast Healthcare Interoperability Resources (FHIR) standard has emerged as a promising mechanis…

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…

Large-language models (LLMs) show promise for extracting information from clinical notes. Deploying these models at scale can be challenging due to high computational costs, regulatory constraints, and privacy concerns. To address these challenges, …

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…

Interpreting medical images and writing radiology reports is a critical yet challenging task in healthcare. Despite their importance, both human-written and AI-generated reports are liable to errors, leaving a need for robust and representative data…

In this work, we extract an event log from the MIMIC-IV-ED dataset by adopting a well-established event log generation methodology, and we name this event log MIMICEL. The data tables in the MIMIC-IV-ED dataset relate to each other based on the exis…

CXR-PRO is an adaptation of the MIMIC-CXR dataset that omits references to prior radiology reports. Consisting of 374,139 free-text radiology reports and associated chest radiographs, CXR-PRO addresses the issue of hallucinated references to priors …

A multimodal combination of the MIMIC-IV v1.0.0 and MIMIC Chest X-ray (MIMIC-CXR-JPG) v2.0.0 databases filtered to only include patients that have at least one chest X-ray performed with the goal of validating multi-modal predictive analytics in hea…

In this project, the MIMIC-IV demo database was used to create an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) instance. The transformation was built making use of template scripts and concept mappings from a previous pr…