Published on in Vol 10, No 4 (2022): April
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/36977, first published
.

Journals
- Li D, Mathews C, Zamarripa C, Zhang F, Xiao Q. Wound tissue segmentation by computerised image analysis of clinical pressure injury photographs: a pilot study. Journal of Wound Care 2022;31(8):710 View
- Eldem H, Ülker E, Yaşar Işıklı O. Encoder–decoder semantic segmentation models for pressure wound images. The Imaging Science Journal 2022;70(2):75 View
- Foltynski P, Ladyzynski P. Internet service for wound area measurement using digital planimetry with adaptive calibration and image segmentation with deep convolutional neural networks. Biocybernetics and Biomedical Engineering 2023;43(1):17 View
- Dweekat O, Lam S, McGrath L. Machine Learning Techniques, Applications, and Potential Future Opportunities in Pressure Injuries (Bedsores) Management: A Systematic Review. International Journal of Environmental Research and Public Health 2023;20(1):796 View
- Solte D, Storck M. Künstliche Intelligenz in der Therapie chronischer Wunden – Konzepte und Ausblick. Gefässchirurgie 2023;28(1):24 View
- Chairat S, Chaichulee S, Dissaneewate T, Wangkulangkul P, Kongpanichakul L. AI-Assisted Assessment of Wound Tissue with Automatic Color and Measurement Calibration on Images Taken with a Smartphone. Healthcare 2023;11(2):273 View
- Sollte D, Storck M. Auf das Training kommt es an. ProCare 2023;28(3):18 View
- Kairys A, Pauliukiene R, Raudonis V, Ceponis J. Towards Home-Based Diabetic Foot Ulcer Monitoring: A Systematic Review. Sensors 2023;23(7):3618 View
- Ramirez-GarciaLuna J, Martinez-Jimenez M, Fraser R, Bartlett R, Lorincz A, Liu Z, Saiko G, Berry G. Is my wound infected? A study on the use of hyperspectral imaging to assess wound infection. Frontiers in Medicine 2023;10 View
- Fergus P, Chalmers C, Henderson W, Roberts D, Waraich A. Pressure Ulcer Categorization and Reporting in Domiciliary Settings Using Deep Learning and Mobile Devices: A Clinical Trial to Evaluate End-to-End Performance. IEEE Access 2023;11:65138 View
- Le D, Pham T. Unveiling the role of artificial intelligence for wound assessment and wound healing prediction. Exploration of Medicine 2023:589 View
- Malik H, Idris A, Toha S, Idris I, Daud M, Tokhi M. Deploying Patch-Based Segmentation Pipeline for Fibroblast Cell Images at Varying Magnifications. IEEE Access 2023;11:98171 View
- Gupta R, Goldstone L, Eisen S, Ramachandram D, Cassata A, Fraser R, Ramirez-GarciaLuna J, Bartlett R, Allport J. Towards an AI-Based Objective Prognostic Model for Quantifying Wound Healing. IEEE Journal of Biomedical and Health Informatics 2024;28(2):666 View
- Dhar M, Zhang T, Patel Y, Gopalakrishnan S, Yu Z. FUSegNet: A deep convolutional neural network for foot ulcer segmentation. Biomedical Signal Processing and Control 2024;92:106057 View
- Georg P, Schmid M, Zahia S, Probst S, Cazzaniga S, Hunger R, Bossart S. Evaluation of a Semi-Automated Wound-Halving Algorithm for Split-Wound Design Studies: A Step towards Enhanced Wound-Healing Assessment. Journal of Clinical Medicine 2024;13(12):3599 View
- Chen M. Progress in the application of artificial intelligence in skin wound assessment and prediction of healing time. American Journal of Translational Research 2024;16(7):2765 View
- Prakashan D, Kaushik A, Gandhi S. Smart sensors and wound dressings: Artificial intelligence-supported chronic skin monitoring – A review. Chemical Engineering Journal 2024;497:154371 View
- Raja M, Pannirselvam V, Srinivasan S, Guhan B, Rayan F. Recent technological advancements in Artificial Intelligence for orthopaedic wound management. Journal of Clinical Orthopaedics and Trauma 2024;57:102561 View
- Deng J, Shi G, Ye Z, Xiao Q, Zhang X, Ren L, Yang F, Wang M. Unveiling and swift diagnosing chronic wound healing with artificial intelligence assistance. Chinese Chemical Letters 2025;36(3):110496 View
- Griffa D, Natale A, Merli Y, Starace M, Curti N, Mussi M, Castellani G, Melandri D, Piraccini B, Zengarini C. Artificial Intelligence in Wound Care: A Narrative Review of the Currently Available Mobile Apps for Automatic Ulcer Segmentation. BioMedInformatics 2024;4(4):2321 View
- Лукащук Б, Шабатура Ю. Methodology for evaluating complex object contour detection accuracy in SLIC-based image segmentation. Scientific Bulletin of UNFU 2024;34(8) View
- Zhang Z, Sheng S, Zhu S, Jin J. Chronic Wound Assessment System Using an Improved UPerNet Model. International Journal of Imaging Systems and Technology 2025;35(1) View
- Reifs Jiménez D, Casanova-Lozano L, Grau-Carrión S, Reig-Bolaño R. Artificial Intelligence Methods for Diagnostic and Decision-Making Assistance in Chronic Wounds: A Systematic Review. Journal of Medical Systems 2025;49(1) View
- Mohammed H, Corcoran K, Lavergne K, Graham A, Gill D, Jones K, Singal S, Krishnamoorthy M, Cassata A, Mannion D, Fraser R. Clinical, Operational, and Economic Benefits of a Digitally Enabled Wound Care Program in Home Health: Quasi-Experimental, Pre-Post Comparative Study. JMIR Nursing 2025;8:e71535 View
- Blake H. Digital wound management: how it works and its potential benefits in wound care practice. Nursing Standard 2025 View
- Cassidy B, McBride C, Kendrick C, Reeves N, Pappachan J, Fernandez C, Chacko E, Brüngel R, Friedrich C, Alotaibi M, AlWabel A, Alderwish M, Lai K, Yap M. An enhanced harmonic densely connected hybrid transformer network architecture for chronic wound segmentation utilising multi-colour space tensor merging. Computers in Biology and Medicine 2025;192:110172 View
Books/Policy Documents
- Chattree Y, Jain R. Opportunities and Risks in AI for Business Development. View
- Das S, Chaudhuri R, Deb S. Computing and Machine Learning. View
- Ghahremani S. Structural, Syntactic, and Statistical Pattern Recognition. View
- Carvalho R, Morgado A, Sampaio A, Vasconcelos M. Applications of Medical Artificial Intelligence. View
- Sarkar S, Das S, Chanda A, Biswas S. Explainable and Responsible Artificial Intelligence in Healthcare. View
Conference Proceedings
- Kuo S, Huang P, Lin C, Li J, Chang M. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Improving Limited Supervised Foot Ulcer Segmentation Using Cross-Domain Augmentation Strategies View
- Antunović A, Nyarko E, Filko D. 2024 International Conference on Smart Systems and Technologies (SST). Wound Tissue Classification: A Comparative Analysis of Deep Neural Network Models View