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

Computer-Aided Diagnosis (235) Mobile Health (mhealth) (3394) Wearable Devices and Sensors (1104) Fitness Trackers and Smart Pedometers/Accelerometers (650) Digital Biomarkers and Digital Phenotyping (268) Methods and Instruments in Medical Informatics (185)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69328, first published .
Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study

Detection and Analysis of Circadian Biomarkers for Metabolic Syndrome Using Wearable Data: Cross-Sectional Study

Authors of this article:

Jeong-Kyun Kim1 Author Orcid Image ;   Sujeong Mun1 Author Orcid Image ;   Siwoo Lee1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Liu J, Zhang L, Yuan Y, Tang J, Liu Y, Xia L, Zhang J. Deep Learning Radiomics Model Based on Computed Tomography Image for Predicting the Classification of Osteoporotic Vertebral Fractures: Algorithm Development and Validation. JMIR Medical Informatics 2025;13:e75665 View
  2. Liu J, Sun P, Yuan Y, Chen Z, Tian K, Gao Q, Li X, Xia L, Zhang J, Xu N. YOLOv12 Algorithm-Aided Detection and Classification of Lateral Malleolar Avulsion Fracture and Subfibular Ossicle Based on CT Images: Multicenter Study. JMIR Medical Informatics 2025;13:e79064 View