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Smartphone-Based Balance Assessment Using Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study explores the potential of smartphones to objectively assess balance, which is crucial for the elderly and individuals recovering from various medical conditions. We propose an innovative methodology to estimate the Modified Clinical Test o...

Unsupervised Gait Assessments of Stroke Patients Using a Smartphone and Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Home-based rehabilitation is a trend of post-stroke lower limb rehabilitation, aimed at a long-term and higher dose of therapy. Unsupervised gait assessments can help therapists to track patients' recovery progress and timely adjust rehabilitation in...

Using Transfer Learning to Refine Object Detection Models for Blind and Low Vision Users.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Object detection models available on smartphones such as YOLOv8 can potentially help identify and locate objects of interest to people who are blind or low vision (pBLV). However, current models may miss crucial objects for pBLV. Here, we compared 5 ...

Evaluation of an artificial intelligence-based decision support for the detection of cutaneous melanoma in primary care: a prospective real-life clinical trial.

The British journal of dermatology
BACKGROUND: Use of artificial intelligence (AI), or machine learning, to assess dermoscopic images of skin lesions to detect melanoma has, in several retrospective studies, shown high levels of diagnostic accuracy on par with - or even outperforming ...

Adapting an artificial intelligence sexually transmitted diseases symptom checker tool for Mpox detection: the HeHealth experience.

Sexual health
Artificial Intelligence (AI) applications have shown promise in the management of pandemics. In response to the global Monkeypox (Mpox) outbreak, the HeHealth.ai team leveraged an existing tool to screen for sexually transmitted diseases (STD) to dev...

The New Emerging Treatment Choice for Major Depressive Disorders: Digital Therapeutics.

Advances in experimental medicine and biology
The chapter provides an in-depth analysis of digital therapeutics (DTx) as a revolutionary approach to managing major depressive disorder (MDD). It discusses the evolution and definition of DTx, their application across various medical fields, regula...

Automatic Chinese Food recognition based on a stacking fusion model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
With commercialization of deep learning models, daily precision dietary record based on images from smartphones becomes possible. This study took advantage of Deep-learning techniques on visual recognition tasks and proposed a big-data-driven Deep-le...

Design and optimization of a TensorFlow Lite deep learning neural network for human activity recognition on a smartphone.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Human Activity Recognition (HAR), using machine learning to identify times spent (for example) walking, sitting, and standing, is widely used in health and wellness wearable devices, in ambient assistant living devices, and in rehabilitation. In this...

Automatic detection of oral cancer in smartphone-based images using deep learning for early diagnosis.

Journal of biomedical optics
SIGNIFICANCE: Oral cancer is a quite common global health issue. Early diagnosis of cancerous and potentially malignant disorders in the oral cavity would significantly increase the survival rate of oral cancer. Previously reported smartphone-based i...