BACKGROUND: The potential for digital interventions in self-management and treatment of mild to moderate eating disorders (EDs) has already been established. However, apps are infrequently recommended by ED therapists to their clients. Those that are...
BACKGROUND: Transvaginal insertion of polypropylene mesh was extensively used in surgical procedures to treat pelvic organ prolapse (POP) due to its cost-efficiency and durability. However, studies have reported a high rate of complications, includin...
Framing the public health burden of firearm violence should include people with secondary exposure to firearm violence beyond acute bodily injury, yet such data are limited. Electronic health record clinical notes, when leveraged through natural lang...
BACKGROUND: Standardized patients (SPs) prepare medical students for difficult conversations with patients. Despite their value, SP-based simulation training is constrained by available resources and competing clinical demands. Researchers are turnin...
BACKGROUND: Monitoring symptoms of bipolar disorder (BD) is a challenge faced by mental health services. Speech patterns are crucial in assessing the current experiences, emotions, and thought patterns of people with BD. Natural language processing (...
BACKGROUND: This research study aimed to detect the vocal features immersed in empathic counselor speech using samples of calls to a mental health helpline service.
BACKGROUND: Serious pulmonary pathologies of infectious, viral, or bacterial origin are accompanied by inflammation and an increase in oxidative stress (OS). In these situations, biological measurements of OS are technically difficult to obtain, and ...
BACKGROUND: Dependent older people or those losing their autonomy are at risk of emergency hospitalization. Digital systems that monitor health remotely could be useful in reducing these visits by detecting worsening health conditions earlier. Howeve...
BACKGROUND: Unlike one-snap data collection methods that only identify high-risk patients, machine learning models using time-series data can predict adverse events and aid in the timely management of cancer.
BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinic...