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Hamed Mahdizadeh, Haleh Ayatollahi, Nafiseh Esmaeili, Kamkar Mehran Kamkar ,
Volume 4, Issue 3 (9-2013)
Abstract

It is more than a decade that teledermatology has been considered as a potential substitute for the face to face visits. To evaluate its quality, the reliability and accuracy of teledermatology diagnoses are compared to those which are made in face to face visits. In this article, the results of the studies which have compared the reliability and accuracy of diagnoses had been made using teledermatology to the face to face visits were reviewed.

Different resources, such as electronic databases and e-journals were used to choose relevant articles related to teledermatology published between 1997 and 2013, and their main focus was on the reliability and accuracy of diagnoses in teledermatology compared to those in the face to face visits.

The reliability and accuracy of diagnoses in teledermatology compared to those in the face to face visits was more than 60%. Moreover, improving the reliability and accuracy depended on different factors, such as image quality, clinical information, differential diagnoses, consultation with other colleagues and gaining their secondary opinions.

It seems that providing adequate clinical information about patients can help to improve the reliability and accuracy of diagnoses in teledermatology. In this case, teledermatology can be used to provide healthcare services for the distant areas and the poor.


Alireza Sadeghi Moghaddam Bijari, Hoda Keshmiri Neghab, Mohammadhasan Soheilifar,
Volume 16, Issue 3 (11-2025)
Abstract

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.


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