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

Decision Support for Health Professionals (1147) Artificial Intelligence (1216) Machine Learning (1401) Clinical Information and Decision Making (1340) Image Recognition and AI in Dermatology (9) Machine Learning from Digital Images in Dermatology (8)

Published on in Vol 9, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22798, first published .
Deep Learning–Assisted Burn Wound Diagnosis: Diagnostic Model Development Study

Deep Learning–Assisted Burn Wound Diagnosis: Diagnostic Model Development Study

Deep Learning–Assisted Burn Wound Diagnosis: Diagnostic Model Development Study

Authors of this article:

Che Wei Chang1, 2 Author Orcid Image ;   Feipei Lai1 Author Orcid Image ;   Mesakh Christian3 Author Orcid Image ;   Yu Chun Chen3 Author Orcid Image ;   Ching Hsu1 Author Orcid Image ;   Yo Shen Chen2 Author Orcid Image ;   Dun Hao Chang2, 4 Author Orcid Image ;   Tyng Luen Roan2 Author Orcid Image ;   Yen Che Yu2 Author Orcid Image
Article Authors Cited by (9) Tweetations (2) Metrics

Journals

  1. Yang S, Huang C, Yen C, Kao Y, Hsiao Y, Yang J, Chang S, Chuang S, Chen H. Machine Learning Approach for Predicting Inhalation Injury in Patients with Burns. Burns 2023 View
  2. Chang C, Ho C, Lai F, Christian M, Huang S, Chang D, Chen Y. Application of multiple deep learning models for automatic burn wound assessment. Burns 2023;49(5):1039 View
  3. Kairys A, Pauliukiene R, Raudonis V, Ceponis J. Towards Home-Based Diabetic Foot Ulcer Monitoring: A Systematic Review. Sensors 2023;23(7):3618 View
  4. Pabitha C, Vanathi B. Dense Mesh RCNN: assessment of human skin burn and burn depth severity. The Journal of Supercomputing 2024;80(1):1331 View
  5. Rozo A, Miskovic V, Rose T, Keersebilck E, Iorio C, Varon C. A Deep Learning Image-to-Image Translation Approach for a More Accessible Estimator of the Healing Time of Burns. IEEE Transactions on Biomedical Engineering 2023;70(10):2886 View
  6. Wilson R, Rowland R, Kennedy G, Campbell C, Joe V, Chin T, Burmeister D, Christy R, Durkin A. Review of machine learning for optical imaging of burn wound severity assessment. Journal of Biomedical Optics 2024;29(02) View
  7. Vakili Ojarood M, Farzan R, Mohsenizadeh S, Torabi H, Yaghoubi T. Deep Learning during burn prehospital care: An evolving perspective. Burns 2024;50(5):1349 View
  8. Rippon M, Fleming L, Chen T, Rogers A, Ousey K. Artificial intelligence in wound care: diagnosis, assessment and treatment of hard-to-heal wounds: a narrative review. Journal of Wound Care 2024;33(4):229 View

Books/Policy Documents

  1. Abela C, Inguanez F. Data Science and Emerging Technologies. View