Intellectual Property India Publishes Patent Application for A System And Method For Ai-Based Dermatological Disease Detection And Skin Health Assessment

MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641076590 A) filed by Meenakshi Academy Of Higher Education And Research on June 20, 2026, for A System And Method For Ai-Based Dermatological Disease Detection And Skin Health Assessment.

Inventors include Dr. Kumaravel; Dr. Rajesh; Logeswari J; Srimathi N; Mahesh Kumar P G; and Anusha K.

The application for the patent was published on July 03, 2026, under issue no. 27/2026.

Abstract: ABSTRACT A System and Method for AI-Based Dermatological Disease Detection and Skin Health Assessment The present disclosure relates to a system and method for AI based dermatological disease detection, multispectral skin health analysis and predictive dermatological analytics. The system comprises a multispectral dermatological imaging module, a skin bioimpedance characterization module, a metabolic skin signature analysis module, a microbiome intelligence module, an environmental trigger assessment module, a memory unit and a processor. The multispectral dermatological imaging module captures information on the skin in the visible and sub-surface regions and the skin bioimpedance characterization module measures physiological parameters of the skin. The metabolic skin signature analysis module assesses metabolic biomarkers, and the microbiome intelligence module assesses indicators related to microbiomes associated with dermatological conditions. The processor allows multi-modal data fusion of imaging, physiological, metabolic, microbial and environmental data for the detection of dermatological abnormalities, classification of diseases, determination of severity levels, prediction of disease progression, prediction of treatment outcomes and generation of personalized dermatological reports. The invention disclosed provides improved diagnostic accuracy, early disease detection, predictive risk assessment, explainable dermatological intelligence and improved clinical decision making by integrated multimodal dermatological analysis.

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