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

Mobile Health and Apps for Maternal and Child Health (187) mHealth for Screening (269) Pediatrics (246) Clinical Information and Decision Making (1721) Design and Formative Evaluation of Mobile Apps (768) Mobile Health (mhealth) (3234) Decision Support for Health Professionals (1388)

Published on in Vol 6 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40463, first published .
Iterative Development, Validation, and Certification of a Smartphone System to Assess Neonatal Jaundice: Development and Usability Study

Iterative Development, Validation, and Certification of a Smartphone System to Assess Neonatal Jaundice: Development and Usability Study

Iterative Development, Validation, and Certification of a Smartphone System to Assess Neonatal Jaundice: Development and Usability Study

Authors of this article:

Anders Aune1, 2 Author Orcid Image ;   Gunnar Vartdal2 Author Orcid Image ;   Gabriela Jimenez Diaz1, 2 Author Orcid Image ;   Lobke Marijn Gierman2 Author Orcid Image ;   Håkon Bergseng3, 4 Author Orcid Image ;   Elisabeth Darj1 Author Orcid Image
Article Authors Cited by (9) Tweetations (3) Metrics

Journals

  1. Kihara T, Sugihara T, Ikeda S, Matsuki Y, Koda H, Onoyama T, Takata T, Nagahara T, Isomoto H. Identification and Quantification of Jaundice by Trans-Conjunctiva Optical Imaging Using a Human Brain-like Algorithm: A Cross-Sectional Study. Diagnostics 2023;13(10):1767 View
  2. Jiménez-Díaz G, Aune A, Elizarrarás-Rivas J, Gierman L, Keitsch M, Marcuzzi A, Infanti J. Neonatal jaundice detection in low-resource Mexican settings: possibilities and barriers for innovation with mobile health. BMC Health Services Research 2024;24(1) View
  3. Omol E, Mburu L, Abuonji P. Digital Maturity Assessment Model (DMAM): assimilation of Design Science Research (DSR) and Capability Maturity Model Integration (CMMI). Digital Transformation and Society 2025;4(2):128 View
  4. Bancone G, Gilder M, Win E, Gornsawun G, Moo P, Archasuksan L, Wai N, Win S, Hanboonkunupakarn B, Nosten F, Carrara V, McGready R. Non-invasive detection of bilirubin concentrations during the first week of life in a low-resource setting along the Thailand–Myanmar border. BMJ Paediatrics Open 2024;8(1):e002754 View
  5. van Kempen E, Vrijlandt S, van der Geest K, Lotgering S, Hueting T, Oostenbrink R. A Blueprint for Clinical-Driven Medical Device Development: The Feverkidstool Application to Identify Children With Serious Bacterial Infection. Mayo Clinic Proceedings: Digital Health 2024;2(4):656 View
  6. Fatoni A, Anggraeni M, Rahmawati E. Non-Invasive Wearable Sensor for Real-Time Neonatal Jaundice Monitoring Using Forehead Skin Tone Analysis. Analytica 2025;6(1):6 View
  7. Jiménez-Díaz G, Gierman L, Keitsch M, Elizarrarás-Rivas J, Silva- Méndez R, Infanti J, Marcuzzi A. Validation of a Mobile Health Device for Neonatal Jaundice Screening: A Cross-Sectional Study in a Resource-Limited Setting in Mexico. Sage Open Pediatrics 2025;12 View
  8. Aune A, Jímenez-Díaz G, Gierman L, Vartdal G, Reyes Berlanga M, Tusoy J, Bergseng H, Shakya S, Darj E. Smartphone-based screening of neonatal jaundice in three populations in low and middle-income countries: a cross-sectional study. BMJ Paediatrics Open 2025;9(1):e002242 View
  9. Park S, Kwon S, Ji Y, Sakthivel H, Leem J, Kwak Y, Huang J, Chiu G, O’Brien A, Konger R, Wang Y, Kim Y. Machine reading and recovery of colors for hemoglobin-related bioassays and bioimaging. Science Advances 2025;11(23) View