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PLOS Digital Health

Interdisciplinary Open Access journal

PLOS Digital Health drives transformation in the delivery of equitable and unbiased healthcare through ethically conducted, impactful, immediately accessible research from our diverse community of engineers, clinicians and researchers, as well as social scientists and industry leaders, from around the world.

PLOS Digital Health is an interdisciplinary Open Access journal publishing boundary-breaking original academic and clinical research that uses open science practices, digital tools, technologies, and data science to significantly advance human health and health care.

This community-driven journal reflects the full breadth of the digital health research environment, including social and ethical issues, with a strong focus on public health and big data management; including but not limited to, e-health, medical imaging and diagnostics, fairness and health disparities as outcomes from digital health research, patient accessibility and behavior, and precision medicine.

We publish primary research articles, commissioned opinions and reviews that explore digital health tools, methods, data and curation that advance healthcare technologies and decision-making or broaden accessible, effective care options for diverse communities around the world. Submissions describing methods, software, databases, or other tools that meet the journal’s criteria for advance, utility, validation, and availability are also welcomed. 

Visit website: https://journals.plos.org/digitalhealth/

 PLOSDigiHealth

Details last updated 03-Nov-2022

PLOS Digital Health News

AI may be better than some doctors at diagnosing eye problems

AI may be better than some doctors at diagnosing eye problems

Independent - 17-Apr-2024

Could help doctors spot eye issues faster and decide who needs urgent care

Phone apps could record six minutes of consecutive walking to predict risk of early death

Phone apps could record six minutes of consecutive walking to predict risk of early death

New Atlas - 20-Oct-2022

The study computes predictive models for risk stratification via population analysis for results