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Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Related Experiment Video

Updated: Mar 27, 2026

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

Published on: February 3, 2022

Smartphone-Based Digital Phenotyping Across Health Conditions: Scoping Review.

Arlen Dumas¹, Joanne Hokayem², Georgia Goodman³

¹Department of Computer Science and Statistics, University of Rhode Island, 9 Greenhouse Road, Kingston, RI, 02881, United States, 1 401-874-4497.

Journal of Medical Internet Research

|March 25, 2026

Summary

This summary is machine-generated.

Smartphone digital phenotyping uses phone sensors to track health behaviors across mental health, physical health, and substance use disorders (SUDs). Improved standardization is needed for clinical use.

Keywords:

digital health digital phenotyping health behaviors mobile phone scoping review smartphones

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Last Updated: Mar 27, 2026

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Area of Science:

Digital Health
Mobile Sensing
Behavioral Science

Background:

Smartphone-based digital phenotyping leverages onboard sensors to passively collect behavioral and environmental data.
Applications are extensive in mental health and chronic disease management.
This review focuses on studies exclusively using smartphone sensors for health characterization.

Conclusions:

This review offers the first comprehensive synthesis of smartphone-only digital phenotyping across diverse health domains.
Findings consolidate observed behavioral associations, aiding researchers in correlating new findings and identifying research gaps.
Highlights the potential of digital phenotyping while emphasizing the need for standardization for clinical translation.