AIMC Topic: Mobile Applications

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Artificial intelligence application versus physical therapist for squat evaluation: a randomized controlled trial.

Scientific reports
Artificial intelligence technology is becoming more prevalent in health care as a tool to improve practice patterns and patient outcomes. This study assessed ability of a commercialized artificial intelligence (AI) mobile application to identify and ...

Automatic detection and monitoring of abnormal skull shape in children with deformational plagiocephaly using deep learning.

Scientific reports
Craniofacial anomaly including deformational plagiocephaly as a result of deformities in head and facial bones evolution is a serious health problem in newbies. The impact of such condition on the affected infants is profound from both medical and so...

Your mileage may vary: impact of data input method for a deep learning bone age app's predictions.

Skeletal radiology
OBJECTIVE: The purpose of this study was to evaluate agreement in predictions made by a bone age prediction application ("app") among three data input methods.

A Review of Digital Innovations for Diet Monitoring and Precision Nutrition.

Journal of diabetes science and technology
This article provides an up-to-date review of technological advances in 3 key areas related to diet monitoring and precision nutrition. First, we review developments in mobile applications, with a focus on food photography and artificial intelligence...

Ambulatory Cardiovascular Monitoring Via a Machine-Learning-Assisted Textile Triboelectric Sensor.

Advanced materials (Deerfield Beach, Fla.)
Wearable bioelectronics for continuous and reliable pulse wave monitoring against body motion and perspiration remains a great challenge and highly desired. Here, a low-cost, lightweight, and mechanically durable textile triboelectric sensor that can...

Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study.

The Lancet. Digital health
BACKGROUND: Self-reported symptoms during the COVID-19 pandemic have been used to train artificial intelligence models to identify possible infection foci. To date, these models have only considered the culmination or peak of symptoms, which is not s...

Artificial intelligence and the future of life sciences.

Drug discovery today
Over the past few decades, the number of health and 'omics-related data' generated and stored has grown exponentially. Patient information can be collected in real time and explored using various artificial intelligence (AI) tools in clinical trials;...

DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization.

Journal of chemical information and modeling
Lead optimization, a critical step in early stage drug discovery, involves making chemical modifications to a small-molecule ligand to improve properties such as binding affinity. We recently developed DeepFrag, a deep-learning model capable of recom...

Understanding Public Perceptions of COVID-19 Contact Tracing Apps: Artificial Intelligence-Enabled Social Media Analysis.

Journal of medical Internet research
BACKGROUND: The emergence of SARS-CoV-2 in late 2019 and its subsequent spread worldwide continues to be a global health crisis. Many governments consider contact tracing of citizens through apps installed on mobile phones as a key mechanism to conta...