AI Medical Compendium Journal:
JMIR mHealth and uHealth

Showing 11 to 20 of 40 articles

Controlled and Real-Life Investigation of Optical Tracking Sensors in Smart Glasses for Monitoring Eating Behavior Using Deep Learning: Cross-Sectional Study.

JMIR mHealth and uHealth
BACKGROUND: The increasing prevalence of obesity necessitates innovative approaches to better understand this health crisis, particularly given its strong connection to chronic diseases such as diabetes, cancer, and cardiovascular conditions. Monitor...

Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.

JMIR mHealth and uHealth
BACKGROUND: Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide diseas...

The Evaluation of Generative AI Should Include Repetition to Assess Stability.

JMIR mHealth and uHealth
The increasing interest in the potential applications of generative artificial intelligence (AI) models like ChatGPT in health care has prompted numerous studies to explore its performance in various medical contexts. However, evaluating ChatGPT pose...

Application of eHealth Tools in Anticoagulation Management After Cardiac Valve Replacement: Scoping Review Coupled With Bibliometric Analysis.

JMIR mHealth and uHealth
BACKGROUND: Anticoagulation management can effectively prevent complications in patients undergoing cardiac valve replacement (CVR). The emergence of eHealth tools provides new prospects for the management of long-term anticoagulants. However, there ...

Effects of User-Reported Risk Factors and Follow-Up Care Activities on Satisfaction With a COVID-19 Chatbot: Cross-Sectional Study.

JMIR mHealth and uHealth
BACKGROUND: The COVID-19 pandemic influenced many to consider methods to reduce human contact and ease the burden placed on health care workers. Conversational agents or chatbots are a set of technologies that may aid with these challenges. They may ...

Availability, Quality, and Evidence-Based Content of mHealth Apps for the Treatment of Nonspecific Low Back Pain in the German Language: Systematic Assessment.

JMIR mHealth and uHealth
BACKGROUND: Nonspecific low back pain (NSLBP) carries significant socioeconomic relevance and leads to substantial difficulties for those who are affected by it. The effectiveness of app-based treatments has been confirmed, and clinicians are recomme...

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.

JMIR mHealth and uHealth
BACKGROUND: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects on mothers and newborns if unaddressed. Predicting next-day physiological or perceived stress can hel...

Emerging Artificial Intelligence-Empowered mHealth: Scoping Review.

JMIR mHealth and uHealth
BACKGROUND: Artificial intelligence (AI) has revolutionized health care delivery in recent years. There is an increase in research for advanced AI techniques, such as deep learning, to build predictive models for the early detection of diseases. Such...

Fully Automated Wound Tissue Segmentation Using Deep Learning on Mobile Devices: Cohort Study.

JMIR mHealth and uHealth
BACKGROUND: Composition of tissue types within a wound is a useful indicator of its healing progression. Tissue composition is clinically used in wound healing tools (eg, Bates-Jensen Wound Assessment Tool) to assess risk and recommend treatment. How...

Deep Learning in mHealth for Cardiovascular Disease, Diabetes, and Cancer: Systematic Review.

JMIR mHealth and uHealth
BACKGROUND: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and cancer impose a significant burden on people and health care systems around the globe. Recently, deep learning (DL) has shown great potential for the development o...