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

Non-Randomized Studies (funded, eHealth) (136) mHealth in a Clinical Setting (768) Mobile Health and Apps for Maternal and Child Health (224) New Diagnostic Tools and Instruments for Pediatrics (51) Screening and Early Diagnosis in Pediatrics (41) Artificial Intelligence (2318) Decision Support for Health Professionals (1625) Machine Learning (2214) Medical imaging (130) mHealth in the Developing World/LMICs, Underserved Communities, and for Global Health (739)

Published on in Vol 14 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65811, first published .
Deep Learning–Based Pattern Recognition for Detecting Penile Abnormalities: Protocol for Developing a Mobile App for Circumcision Eligibility

Deep Learning–Based Pattern Recognition for Detecting Penile Abnormalities: Protocol for Developing a Mobile App for Circumcision Eligibility

Deep Learning–Based Pattern Recognition for Detecting Penile Abnormalities: Protocol for Developing a Mobile App for Circumcision Eligibility

Authors of this article:

Irfan Wahyudi1 Author Orcid Image ;   Chandra Prasetyo Utomo2 Author Orcid Image ;   Samsuridjal Djauzi3 Author Orcid Image ;   Muhamad Fathurahman2 Author Orcid Image ;   Gerhard Reinaldi Situmorang1 Author Orcid Image ;   Arry Rodjani1 Author Orcid Image ;   Putu Angga Risky Raharja1 Author Orcid Image ;   Kevin Yonathan1 Author Orcid Image ;   Budi Santoso1 Author Orcid Image ;   Dwidian Khresna1 Author Orcid Image ;   Marco Raditya1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Wahyudi I, Utomo C, Djauzi S, Fathurahman M, Situmorang G, Rodjani A, Raharja P, Yonathan K, Santoso B, Khresna D, Raditya M. Correction: Deep Learning–Based Pattern Recognition for Detecting Penile Abnormalities: Protocol for Developing a Mobile App for Circumcision Eligibility. JMIR Research Protocols 2026;15:e89351 View