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

Formative Evaluation of Digital Health Interventions (2491) Decision Support for Health Professionals (1210) Machine Learning (1501) Clinical Information and Decision Making (1434)

Published on in Vol 6, No 5 (2022): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34830, first published .
Machine Learning Decision Support for Detecting Lipohypertrophy With Bedside Ultrasound: Proof-of-Concept Study

Machine Learning Decision Support for Detecting Lipohypertrophy With Bedside Ultrasound: Proof-of-Concept Study

Machine Learning Decision Support for Detecting Lipohypertrophy With Bedside Ultrasound: Proof-of-Concept Study

Authors of this article:

Ela Bandari1 Author Orcid Image ;   Tomas Beuzen1 Author Orcid Image ;   Lara Habashy1 Author Orcid Image ;   Javairia Raza1 Author Orcid Image ;   Xudong Yang1 Author Orcid Image ;   Jordanna Kapeluto2, 3 Author Orcid Image ;   Graydon Meneilly2, 4 Author Orcid Image ;   Kenneth Madden2, 4, 5 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Huang J, Yeung A, Kerr D, Gentile S, Heinemann L, Al-Sofiani M, Joseph J, Seley J, Klonoff D. Lipohypertrophy and Insulin: An Old Dog That Needs New Tricks. Endocrine Practice 2023;29(8):670 View
  2. Lee H, Lee Y, Jung S, Lee S, Oh B, Yang S. Deep Learning-Based Evaluation of Ultrasound Images for Benign Skin Tumors. Sensors 2023;23(17):7374 View
  3. Zhou Q, Zhang Y, Yao W, Liang S, Feng H, Pan H. Effects of proprioceptive neuromuscular facilitation combined with threshold inspiratory muscle training on respiratory function in neurocritical patients with weaning failure: a randomized controlled trial. International Journal of Rehabilitation Research 2024;47(3):164 View