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Generating Artificial Patients With Reliable Clinical Characteristics Using a Geometry-Based Variational Autoencoder: Proof-of-Concept Feasibility Study

Generating Artificial Patients With Reliable Clinical Characteristics Using a Geometry-Based Variational Autoencoder: Proof-of-Concept Feasibility Study

Fabrice Ferré, Stéphanie Allassonnière, Clément Chadebec, Vincent Minville

J Med Internet Res 2025;27:e63130

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Authors’ Reply: Promoting Oral Health Literacy Among UAE Public Sector Employees

Authors’ Reply: Promoting Oral Health Literacy Among UAE Public Sector Employees

Florence Carrouel, Benjamin du Sartz de Vigneulles, Céline Clément, Virginie-Eve Lvovschi, Elise Verot, Valeria Tantardini, Michel Lamure, Denis Bourgeois, Claude Dussart, Romain Lan

JMIR Public Health Surveill 2024;10:e67634

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French Version of the User Mobile Application Rating Scale: Adaptation and Validation Study

French Version of the User Mobile Application Rating Scale: Adaptation and Validation Study

Ina Saliasi, Romain Lan, Maryem Rhanoui, Laurie Fraticelli, Stéphane Viennot, Delphine Tardivo, Céline Clément, Benjamin du Sartz de Vigneulles, Sandie Bernard, Adeline Darlington-Bernard, Claude Dussart, Denis Bourgeois, Florence Carrouel

JMIR Mhealth Uhealth 2024;12:e63776

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Impact of a Self-Autonomous Evaluation Station and Personalized Training Algorithm on Quality of Life and Physical Capacities in Sedentary Adults: Randomized Controlled Trial

Impact of a Self-Autonomous Evaluation Station and Personalized Training Algorithm on Quality of Life and Physical Capacities in Sedentary Adults: Randomized Controlled Trial

Yann Le Mat, Corentin Casali, Franck Le Mat, Léonard Féasson, Clément Foschia, Mathias Géry, Jérémy Rossi, Guillaume Y Millet

JMIR Form Res 2024;8:e45461

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Promoting Health Literacy in the Workplace Among Civil Servants: Cross-Sectional Study

Promoting Health Literacy in the Workplace Among Civil Servants: Cross-Sectional Study

The sample size was calculated based on the results of the studies of Sabbahi et al [28], Ramlay et al [29] and Clément et al [30]. The 2-mean formula was applied, with α=.05, power=80%, SD=18, expected difference=10, and expected dropout rate=20%, giving n=51 per group for each professional category of French civil servant (A, B, and C); thus, the total sample size required was 153 participants.

Florence Carrouel, Benjamin du Sartz de Vigneulles, Céline Clément, Virginie-Eve Lvovschi, Elise Verot, Valeria Tantardini, Michel Lamure, Denis Bourgeois, Romain Lan, Claude Dussart

JMIR Public Health Surveill 2024;10:e58942

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An Escape Game on University Students’ Mental Health During the COVID-19 Pandemic: Cocreation Study

An Escape Game on University Students’ Mental Health During the COVID-19 Pandemic: Cocreation Study

David Labrosse, Clara Vié, Hana Hajjam, Clément Tisseron, Dimitri Thellier, Ilaria Montagni

JMIR Serious Games 2024;12:e48545

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Sleep Disorders and Quality of Life in Patients With Cancer: Prospective Observational Study of the Rafael Institute

Sleep Disorders and Quality of Life in Patients With Cancer: Prospective Observational Study of the Rafael Institute

Nathaniel Scher, Liath Guetta, Clément Draghi, Safia Yahiaoui, Mathilde Terzioglu, Emilie Butaye, Kathy Henriques, Marie Alavoine, Ayala Elharar, Andre Guetta, Alain Toledano

JMIR Form Res 2022;6(11):e37371

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Estimating the Proportion of COVID-19 Contacts Among Households Based on Individuals With Myocardial Infarction History: Cross-sectional Telephone Survey

Estimating the Proportion of COVID-19 Contacts Among Households Based on Individuals With Myocardial Infarction History: Cross-sectional Telephone Survey

Laurie Fraticelli, Julie Freyssenge, Clément Claustre, Mikaël Martinez, Abdesslam Redjaline, Patrice Serre, Thomas Bochaton, Carlos El Khoury

JMIR Form Res 2021;5(4):e26955

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Identification of the Best Semantic Expansion to Query PubMed Through Automatic Performance Assessment of Four Search Strategies on All Medical Subject Heading Descriptors: Comparative Study

Identification of the Best Semantic Expansion to Query PubMed Through Automatic Performance Assessment of Four Search Strategies on All Medical Subject Heading Descriptors: Comparative Study

Clément R Massonnaud, Gaétan Kerdelhué, Julien Grosjean, Romain Lelong, Nicolas Griffon, Stefan J Darmoni

JMIR Med Inform 2020;8(6):e12799

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Word Embedding for the French Natural Language in Health Care: Comparative Study

Word Embedding for the French Natural Language in Health Care: Comparative Study

Emeric Dynomant, Romain Lelong, Badisse Dahamna, Clément Massonnaud, Gaétan Kerdelhué, Julien Grosjean, Stéphane Canu, Stefan J Darmoni

JMIR Med Inform 2019;7(3):e12310

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