Skin Sight Pro: Multi-Species Dermatology Assistant

The number of skin ailments faced by humans and animals is rising rapidly, indicating that there is an urgent need for intelligent, accessible diagnostic systems. Expert consultation is required to perform dermatological diagnoses through traditional means; however, they are often not available in many regions, causing delays to begin treatment. As a solution, Skin Sight Pro will serve as a multi-species dermatology assistant for real-time skin disease diagnosis using imaging techniques and deep learning thus allowing for diagnosis from images. Processing of input images will occur using computer vision and convolutional neural networks to derive accurate classifications of skin disease type and location. The system allows skin analysis for both humans and animals and has the capability to support both automatic subject identification (for example) through use of a dual-mode detection system that allows the user to choose between two different methods for identification (e.g., manual selection or automatic subject identification). The application of image processing techniques (e.g., resizing, normalizing and enhancing) will enhance the accuracy of classification results Once the system has diagnosed an organism based on skin type, it will generate a complete prescription that includes both the medications prescribed, the amount to use per dose and any precautions that may be necessary, as well as follow-up recommendations. In addition to prescriptions, user authentication and history tracking are built-in features of the platform, which will assist with maintaining patient records more efficiently. As such, the implementation of this proposed solution will provide benefits including greater reduction in the amount of time between the onset of skin disease diagnosis and treatment, improved access to dermatological care, as well as an intelligent support system for both medical and veterinary uses.

Authors

Publication Details

Journal
Iconic Research and Engineering Journals
Published
2026-04-10
DOI
https://doi.org/10.64388/irev9i10-1716177
Primary Topic
Cutaneous Melanoma Detection and Management
Type
article
Field-Weighted Citation Impact
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article

Skin Sight Pro: Multi-Species Dermatology Assistant

Priyadharshini S, Thamarai Selvan S, Parthasarathy P
Iconic Research and Engineering Journals
Cutaneous Melanoma Detection and Management
article

Skin Sight Pro: Multi-Species Dermatology Assistant

Priyadharshini S, Thamarai Selvan S, Parthasarathy P
article en

Abstract

The number of skin ailments faced by humans and animals is rising rapidly, indicating that there is an urgent need for intelligent, accessible diagnostic systems. Expert consultation is required to perform dermatological diagnoses through traditional means; however, they are often not available in many regions, causing delays to begin treatment. As a solution, Skin Sight Pro will serve as a multi-species dermatology assistant for real-time skin disease diagnosis using imaging techniques and deep learning thus allowing for diagnosis from images. Processing of input images will occur using computer vision and convolutional neural networks to derive accurate classifications of skin disease type and location. The system allows skin analysis for both humans and animals and has the capability to support both automatic subject identification (for example) through use of a dual-mode detection system that allows the user to choose between two different methods for identification (e.g., manual selection or automatic subject identification). The application of image processing techniques (e.g., resizing, normalizing and enhancing) will enhance the accuracy of classification results Once the system has diagnosed an organism based on skin type, it will generate a complete prescription that includes both the medications prescribed, the amount to use per dose and any precautions that may be necessary, as well as follow-up recommendations. In addition to prescriptions, user authentication and history tracking are built-in features of the platform, which will assist with maintaining patient records more efficiently. As such, the implementation of this proposed solution will provide benefits including greater reduction in the amount of time between the onset of skin disease diagnosis and treatment, improved access to dermatological care, as well as an intelligent support system for both medical and veterinary uses.

Iconic Research and Engineering JournalsVol. 9(10)
Openalex Percentile: Top 6%
Cutaneous Melanoma Detection and Management
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