Resources

Pacing artifacts in electrocardiogram (ECG) signals can interfere with accurate waveform analysis, making their detection and removal essential for reliable interpretation. We present an algorithm and provide MATLAB code to detect and remove pacing …

This dataset is an extension of the Gesture Recognition and Biometrics Electromyogram (GRABMyo) dataset, a comprehensive collection of surface electromyography (sEMG) signals from the forearm and wrist while performing static gestures, designed for …

Glaucomatous optic neuropathy (GON) is a leading cause of irreversible blindness worldwide, affecting an estimated 64.3 million people globally with projections reaching 111.8 million by 2040. Approximately 50% of cases remain undiagnosed until adva…

Intraoperative cardiac arrhythmias present distinct characteristics and clinical challenges compared to non-surgical environments, yet publicly available electrocardiogram (ECG) databases have primarily focused on ambulatory and intensive care envir…

This dataset, named PolySomnoGraphic Inter-scorer Performance Assessment (PSG-IPA) database, comprises 20 polysomnography (PSG) recordings and related multi-expert scoring annotations. It was utilized in a study to evaluate inter-scorer variability,…

Clinical risk prediction based on machine learning algorithms plays a vital role in modern healthcare. A crucial component in developing a reliable prediction model is a high-quality dataset with time series clinical events. In this work, we release…

CXR-Align is a benchmark dataset designed to evaluate vision-language processing (VLP) models' ability to accurately interpret negations in chest X-ray (CXR) reports. Negations are prevalent in medical documentation and pose significant challenges f…

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…

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…

Minimally invasive image-guided surgery heavily relies on vision. Deep learning models for surgical video analysis can support surgeons in visual tasks such as assessing the critical view of safety (CVS) in laparoscopic cholecystectomy, potentially …