AI-Powered Skin Disease Detection with IKS-Inspired Remedies

Abstract

Skin conditions rank among the most widespread health problems worldwide and typically demand prompt diagnosis and effective treatment to avoid serious complications. Traditional clinical diagnosis faces several significant obstacles, including limited access to qualified dermatologists, varying levels of medical expertise among practitioners, and potential misreading of symptoms and visual signs.

This research presents a proposed solution to address these critical gaps through an artificial intelligence-powered diagnostic system specifically designed for skin disease identification. The innovative system incorporates treatment recommendations based on Indigenous Knowledge Systems, creating a unique blend of technological advancement and traditional healing wisdom. The approach leverages human understanding of pattern recognition in skin appearance to identify various dermatological conditions while supporting clinical decision-making through sophisticated computer-based analytical tools. Researchers trained and evaluated this system using a carefully assembled dataset that represents a broad spectrum of skin diseases and conditions. Beyond simply identifying the specific disease, the system provides comprehensive treatment suggestions that merge traditional Indigenous Knowledge Systems with contemporary medical approaches. This integration promotes a more complete and patient-focused healthcare methodology that respects cultural practices while maintaining medical effectiveness. Experimental testing demonstrates impressive accuracy rates in disease classification, with additional explainability features that enhance clinical reliability and build trust among medical professionals. These transparency mechanisms help doctors understand how the system reaches its diagnostic conclusions, supporting more confident treatment decisions. The convergence of Indigenous Knowledge Systems and artificial intelligence technology creates an innovative, equitable, and culturally appropriate healthcare solution. This approach proves especially valuable in rural and underserved communities where access to specialized medical care remains limited, offering hope for improved health outcomes across diverse populations.