Published on in Vol 6, No 6 (2018): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9834, first published .
A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study

A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study

A New Influenza-Tracking Smartphone App (Flu-Report) Based on a Self-Administered Questionnaire: Cross-Sectional Study

Journals

  1. Inomata T, Iwagami M, Nakamura M, Shiang T, Yoshimura Y, Fujimoto K, Okumura Y, Eguchi A, Iwata N, Miura M, Hori S, Hiratsuka Y, Uchino M, Tsubota K, Dana R, Murakami A. Characteristics and Risk Factors Associated With Diagnosed and Undiagnosed Symptomatic Dry Eye Using a Smartphone Application. JAMA Ophthalmology 2020;138(1):58 View
  2. Aslani N, Lazem M, Mahdavi S, Garavand A. A Review of Mobile Health Applications in Epidemic and Pandemic Outbreaks: Lessons Learned for COVID-19. Archives of Clinical Infectious Diseases 2020;15(4) View
  3. Kim M, Yune S, Chang S, Jung Y, Sa S, Han H. The Fever Coach Mobile App for Participatory Influenza Surveillance in Children: Usability Study. JMIR mHealth and uHealth 2019;7(10):e14276 View
  4. Inomata T, Sung J, Nakamura M, Fujisawa K, Muto K, Ebihara N, Iwagami M, Nakamura M, Fujio K, Okumura Y, Okano M, Murakami A. New medical big data for P4 medicine on allergic conjunctivitis. Allergology International 2020;69(4):510 View
  5. Leal Neto O, Cruz O, Albuquerque J, Nacarato de Sousa M, Smolinski M, Pessoa Cesse E, Libel M, Vieira de Souza W. Participatory Surveillance Based on Crowdsourcing During the Rio 2016 Olympic Games Using the Guardians of Health Platform: Descriptive Study. JMIR Public Health and Surveillance 2020;6(2):e16119 View
  6. Kleber G, Alves D, Paiva J, Diógenes D, Valentim R, Medeiros A. SOS Syphilis: smartphone application for the mapping of syphilis attention networks.. Procedia Computer Science 2021;181:434 View
  7. Inomata T, Sung J, Nakamura M, Iwagami M, Okumura Y, Iwata N, Midorikawa-Inomata A, Fujimoto K, Eguchi A, Nagino K, Fujio K, Miura M, Shokirova H, Murakami A. Using Medical Big Data to Develop Personalized Medicine for Dry Eye Disease. Cornea 2020;39(1):S39 View
  8. Asadzadeh A, Kalankesh L. A scope of mobile health solutions in COVID-19 pandemics. Informatics in Medicine Unlocked 2021;23:100558 View
  9. Nishioka Y, Noda T, Okada S, Myojin T, Kubo S, Higashino T, Nakajima H, Sugiyama T, Ishii H, Imamura T. Association between influenza and the incidence rate of new‐onset type 1 diabetes in Japan. Journal of Diabetes Investigation 2021 View
  10. Salehinejad S, Niakan Kalhori S, Hajesmaeel Gohari S, Bahaadinbeigy K, Fatehi F. A review and content analysis of national apps for COVID-19 management using Mobile Application Rating Scale (MARS). Informatics for Health and Social Care 2021;46(1):42 View
  11. Zhang M, Chow A, Ho R, Smith H. An Overview of Commercially Available Apps in the Initial Months of the COVID-19 Pandemic. Frontiers in Psychiatry 2021;12 View
  12. Zigman Suchsland M, Rahmatullah I, Lutz B, Lyon V, Huang S, Kline E, Graham C, Cooper S, Su P, Smedinghoff S, Chu H, Sewalk K, Brownstein J, Thompson M. Evaluating an app-guided self-test for influenza: lessons learned for improving the feasibility of study designs to evaluate self-tests for respiratory viruses. BMC Infectious Diseases 2021;21(1) View
  13. Chen Q, Tsubaki M, Minami Y, Fujibayashi K, Yumoto T, Kamei J, Yamada Y, Kominato H, Oono H, Naito T. Using Mobile Phone Data to Estimate the Relationship between Population Flow and Influenza Infection Pathways. International Journal of Environmental Research and Public Health 2021;18(14):7439 View