The MIMIC-IV dataset is an extensive health-related database collected from patients admitted to the intensive care units (ICUs) at the Beth Israel Deaconess Medical Center (BIDMC) between 2008 and 2019. It includes a wide range of data such as patient demographics, vital signs, laboratory test results, procedures, medications, and outcomes. This dataset is instrumental for research in critical care medicine, offering detailed insights into patient care and clinical outcomes in the ICU.
Reference link: https://mimic.mit.edu/docs/
K-MIMIC (Korea Medical Information Mart for Intensive Care) is an extensive health-related database derived from patients who were admitted to the intensive care units (ICUs) of hospitals in Korea. This database has been established through the support of a grant from the Korea Health Technology R&D Project, managed by the Korea Health Industry Development Institute (KHIDI), and funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI21C1074).
K-MIMIC comprises a wide range of data, including electronic medical records, medical images, and vital sign information, serving as a crucial resource for research and development in the field of intensive care medicine.
Reference link: https://sites.google.com/view/k-mimic
The dataset was obtained from non-cardiac surgery patients, including those undergoing general, thoracic, urologic, and gynecologic procedures, who had either routine or emergency surgeries. These surgeries were conducted in 10 operating rooms over the course of one year, from August 2016 to July 2017, at a single academic hospital, Seoul National University Hospital, located in Seoul, Republic of Korea. This dataset provides a comprehensive overview of surgical practices and patient outcomes in a high-volume, academic medical center.
Reference link: https://vitaldb.net/dataset/
The INSPIRE dataset is a comprehensive collection of perioperative medical data from adult surgical cases at Seoul National University Hospital (SNUH) between 2011 and 2020. This dataset encompasses 131,109 cases involving 99,900 patients aged between 18 and 90, all of whom underwent various surgical procedures under anesthesia. It provides extensive information that includes patient demographics, surgical details, and anesthesia records, serving as a valuable resource for research in perioperative medicine and anesthesiology.
Reference link: https://physionet.org/content/inspire/1.2/
The KMLE dataset covers the medical national examination questions from 2019 to 2023, providing detailed yearly data. This dataset includes the question numbers, types, contents, options, correct answers, R-type status, and the presence of images. It is an essential resource for understanding the structure and content of Korea’s medical licensing examinations, aiding in the analysis and improvement of medical education and assessment standards.
Reference link: https://huggingface.co/datasets/sean0042/KorMedMCQA
