AIMC Topic: Smartphone
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Use of Mobile Sensing Data for Longitudinal Monitoring and Prediction of Depression Severity: Systematic Review.
Journal of medical Internet research
Aug 21, 2025
BACKGROUND: Depression is highly recurrent and heterogeneous. The unobtrusive, continuous collection of mobile sensing data via smartphones and wearable devices offers a promising approach to monitor and predict individual depression trajectories, di...
Digitally Enabled AI-Interpreted Salivary Ferning-Based Ovulation Prediction: Feasibility Study.
Journal of medical Internet research
Aug 5, 2025
BACKGROUND: Females with irregular or unpredictable cycles, including those with polycystic ovary syndrome (PCOS), have limited options for validated at-home ovulation prediction. The majority of over-the-counter ovulation prediction kits use urinary...
New Release of User-Captured Images from the Oregon Health & Science University Melanoma MoleMapper Project.
Scientific data
Aug 2, 2025
We announce the release of the OHSU MoleMapper Smartphone Skin Images dataset which contains over six years of new data acquired from the Oregon Health & Science University's (OHSU) MoleMapper study. This released dataset includes 27,499 mole images ...
Data Collection for Automatic Depression Identification in Spanish Speakers Using Deep Learning Algorithms: Protocol for a Case-Control Study.
JMIR research protocols
Jul 31, 2025
BACKGROUND: Depression is a mental health condition that affects millions of people worldwide. Although common, it remains difficult to diagnose due to its heterogeneous symptomatology. Mental health questionnaires are currently the most used assessm...
Digital Therapeutics in Cardiovascular Healthcare: A Narrative Review.
Current cardiology reports
Jul 31, 2025
The rapid development of digital therapeutics (DTx) presents opportunities for cardiovascular diseases (CVD) intervention. This review aims to summarize the technologies and applications of DTx in the field of cardiovascular healthcare. It seeks to i...
AI-driven skin cancer detection from smartphone images: A hybrid model using ViT, adaptive thresholding, black-hat transformation, and XGBoost.
PloS one
Jul 28, 2025
Skin cancer is a significant global public health issue, with millions of new cases identified each year. Recent breakthroughs in artificial intelligence, especially deep learning, possess considerable potential to enhance the accuracy and efficiency...
Application of image guided analyses to monitor fecal microbial composition and diversity in a human cohort.
Scientific reports
Jul 19, 2025
The critical role of gut microbiota in human health and disease has been increasingly illustrated over the past decades, with a significant amount of research demonstrating an unmet need for self-monitor of the fecal microbial composition in an easil...
Video-based pupillometry using Fourier Mellin image correlation.
Scientific reports
Jul 18, 2025
We introduce a novel method for evaluating the pupil light reflex (PLR) response using digital video recordings. Expensive, specialized devices are replacing traditional penlight tests in emergency and neurotrauma departments, but they are not widely...
Finger drawing on smartphone screens enables early Parkinson's disease detection through hybrid 1D-CNN and BiGRU deep learning architecture.
PloS one
Jul 14, 2025
BACKGROUND: Parkinson's disease (PD), a progressive neurodegenerative disorder prevalent in aging populations, manifests clinically through characteristic motor impairments including bradykinesia, rigidity, and resting tremor. Early detection and tim...
PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorders.
BMJ open
Jul 10, 2025
INTRODUCTION: Cognitive behavioural therapy (CBT) serves as a first-line treatment for internalising disorders (ID), encompassing depressive, anxiety or obsessive-compulsive disorders. Nonetheless, a substantial proportion of patients do not experien...
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