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PLOS Digital Health|December 20, 2024
Does providing atrial fibrillation patients, after pulmonary vein isolation, with a 1-lead ECG device relieve the emergency department?-A historically controlled prospective trialJasper L Selder, Mark J Mulder, Willem R van de Vijver, et al.
PLOS Digital Health|December 18, 2024
The feasibility of a visuo-cognitive training intervention using a mobile application and exercise with stroboscopic glasses in Parkinson's: Findings from a pilot randomised controlled trialJulia Das, Gill Barry, Richard Walker, et al.
PLOS Digital Health|January 8, 2025
A mobile intervention to reduce anxiety among university students, faculty, and staff: Mixed methods study on users' experiencesSarah Livermon, Audrey Michel, Yiyang Zhang, et al.
PLOS Digital Health|December 26, 2024
Multicenter comparative analysis of local and aggregated data training strategies in COVID-19 outcome prediction with Machine learningCarine Savalli, Roberta Moreira Wichmann, Fabiano Barcellos Filho, et al.
PLOS Digital Health|January 15, 2025
Natural language processing to evaluate texting conversations between patients and healthcare providers during COVID-19 Home-Based Care in Rwanda at scaleRichard T Lester, Matthew Manson, Muhammed Semakula, et al.
PLOS Digital Health|January 13, 2025
Epidemiological methods in transition: Minimizing biases in classical and digital approachesSara Mesquita, Lília Perfeito, Daniela Paolotti, et al.
PLOS Digital Health|January 9, 2025
A data management system for precision medicineJohn J L Jacobs, Inés Beekers, Inge Verkouter, et al.
PLOS Digital Health|February 5, 2025
Community perspectives regarding brain-computer interfaces: A cross-sectional study of community-dwelling adults in the UKAusten El-Osta, Mahmoud Al Ammouri, Shujhat Khan, et al.
PLOS Digital Health|February 5, 2025
An AI-based approach to predict delivery outcome based on measurable factors of pregnant mothersMichael Owusu-Adjei, James Ben Hayfron-Acquah, Twum Frimpong, et al.
PLOS Digital Health|February 12, 2025
Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settingsIoana Duta, Symon M Kariuki, Anthony K Ngugi, et al.
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