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Object Identification and Safe Route Recommendation Based on Human Flow for the Visually Impaired.

Sensors (Basel, Switzerland)
It is difficult for visually impaired people to move indoors and outdoors. In 2018, world health organization (WHO) reported that there were about 253 million people around the world who were moderately visually impaired in distance vision. A navigat...

Personalized prediction of smartphone-based psychotherapeutic micro-intervention success using machine learning.

Journal of affective disorders
BACKGROUND: Tailoring healthcare to patients' individual needs is a central goal of precision medicine. Combining smartphone-based interventions with machine learning approaches may help attaining this goal. The aim of our study was to explore the pr...

Intelligent Sensing to Inform and Learn (InSTIL): A Scalable and Governance-Aware Platform for Universal, Smartphone-Based Digital Phenotyping for Research and Clinical Applications.

Journal of medical Internet research
In this viewpoint we describe the architecture of, and design rationale for, a new software platform designed to support the conduct of digital phenotyping research studies. These studies seek to collect passive and active sensor signals from partici...

A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset.

Computers in biology and medicine
The automatic recognition of human falls is currently an important topic of research for the computer vision and artificial intelligence communities. In image analysis, it is common to use a vision-based approach for fall detection and classification...

Accuracy of a smartphone application for triage of skin lesions based on machine learning algorithms.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Machine learning algorithms achieve expert-level accuracy in skin lesion classification based on clinical images. However, it is not yet shown whether these algorithms could have high accuracy when embedded in a smartphone app, where imag...

Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions.

JAMA network open
IMPORTANCE: A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy of melanoma diagnoses throughout the patient pathway are needed to reduce the pressure on secondary care and ...

Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears.

IEEE journal of biomedical and health informatics
OBJECTIVE: This work investigates the possibility of automated malaria parasite detection in thick blood smears with smartphones.

Development and accuracy of an artificial intelligence algorithm for acne grading from smartphone photographs.

Experimental dermatology
We developed an artificial intelligence algorithm (AIA) for smartphones to determine the severity of facial acne using the GEA scale and to identify different types of acne lesion (comedonal, inflammatory) and postinflammatory hyperpigmentation (PIHP...

Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol.

BMC psychiatry
BACKGROUND: The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies to collect data and extract relevant information's for patient management. Artificial intelligence (AI) techniques allow processing o...