This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3347) Public (e)Health, Digital Epidemiology and Public Health Informatics (1051) JMIR Theme Issue: COVID-19 Special Issue (2559) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1544) Outbreak and Pandemic Preparedness and Management (1838) Infectious Diseases (non-STD/STI) (1738) Machine Learning (2166) Surveillance Systems (519)

Published on in Vol 6, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35181, first published .
Impact of a Conformité Européenne (CE) Certification–Marked Medical Software Sensor on COVID-19 Pandemic Progression Prediction: Register-Based Study Using Machine Learning Methods

Impact of a Conformité Européenne (CE) Certification–Marked Medical Software Sensor on COVID-19 Pandemic Progression Prediction: Register-Based Study Using Machine Learning Methods

Impact of a Conformité Européenne (CE) Certification–Marked Medical Software Sensor on COVID-19 Pandemic Progression Prediction: Register-Based Study Using Machine Learning Methods

Authors of this article:

Leevi Limingoja1 Author Orcid Image ;   Kari Antila2 Author Orcid Image ;   Vesa Jormanainen1, 3 Author Orcid Image ;   Joel Röntynen4 Author Orcid Image ;   Vilma Jägerroos4 Author Orcid Image ;   Leena Soininen5 Author Orcid Image ;   Hanna Nordlund6 Author Orcid Image ;   Kristian Vepsäläinen3, 7 Author Orcid Image ;   Risto Kaikkonen4 Author Orcid Image ;   Tea Lallukka1 Author Orcid Image
Article Authors Cited by (2) Tweetations (12) Metrics

Journals

  1. Liu V, Koskela T, Kaila M. User-Initiated Symptom Assessment With an Electronic Symptom Checker: Protocol for a Mixed Methods Validation Study. JMIR Research Protocols 2023;12:e41423 View
  2. Wang P, Tian J, Zheng G, Chen Y, Ren X. Application of artificial intelligence in head and neck squamous cell carcinoma. Annals of Medicine 2026;58(1) View