Volume 16, Issue 3 (Volume 16, No 3 2025)
jdc 2025, 16(3): 197-211 |
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Sadeghi Moghaddam Bijari A, Keshmiri Neghab H, Soheilifar M. Applications of artificial intelligence in wound management: a review. jdc 2025; 16 (3) :197-211
URL: http://jdc.tums.ac.ir/article-1-5812-en.html
URL: http://jdc.tums.ac.ir/article-1-5812-en.html
1- Institute of Biochemistry and Biophysics, Tehran university, Tehran, Iran
2- Department of Medical Laser, Yara Institute of Medical Laser Research Center, ACECR, Tehran, Iran ,hodakeshmiri@ut.ac.ir
3- Department of Medical Laser, Yara Institute of Medical Laser Research Center, ACECR, Tehran, Iran
2- Department of Medical Laser, Yara Institute of Medical Laser Research Center, ACECR, Tehran, Iran ,
3- Department of Medical Laser, Yara Institute of Medical Laser Research Center, ACECR, Tehran, Iran
Abstract: (492 Views)
The treatment of wounds has historically been a significant challenge in medicine, incurring substantial financial and emotional costs for both governments and patients. Consequently, researchers have continuously sought novel methods to enhance the wound healing process. In recent years, with the advancements in computer science and the emergence of Artificial Intelligence (AI), many professional fields, including medical sciences, have undergone transformations. There has been a general effort to utilize AI as an assistant or even a human replacement in certain processes. In the field of wound care, the application of AI-based tools is expected to improve the speed and accuracy of the treatment system, leading to faster wound healing and better outcomes for patients.
AI has been presented in various models, each operating on different datasets and employed in diverse research studies. Both software and hardware tools based on AI have been designed and introduced in several investigations. Their performance has been evaluated at various levels, from laboratory to clinical settings, and their efficacy has been demonstrated.
Based on the findings, it can be stated that AI can provide effective assistance to clinical and research staff in the diagnostic, therapeutic, and educational processes of wound treatment. In some cases, it may even reduce the need for direct clinical staff involvement for patients.
AI has been presented in various models, each operating on different datasets and employed in diverse research studies. Both software and hardware tools based on AI have been designed and introduced in several investigations. Their performance has been evaluated at various levels, from laboratory to clinical settings, and their efficacy has been demonstrated.
Based on the findings, it can be stated that AI can provide effective assistance to clinical and research staff in the diagnostic, therapeutic, and educational processes of wound treatment. In some cases, it may even reduce the need for direct clinical staff involvement for patients.
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