The Use of Computer Algorithm to Identify Genetic Markers Related to Skin Diseases and Conditions

Abstract

Roberto Grobman

Skin, as the body's largest organ system, plays a pivotal role in the timely diagnosis and treatment of various dermatological conditions. Traditionally, diagnostics relied on clinical symptoms and the expertise of medical practitioners. However, recent technological advancements have opened new avenues for more precise and early skin condition diagnoses. The integration of skin imaging techniques and deep learning methodologies has revolutionized the field, enabling the early identification of skin disorders and subsequently leading to improved prognoses. Furthermore, artificial intelligence (AI) techniques have been instrumental in clinical genomics, aiding in the identification of genetic markers associated with predisposed conditions, including melanoma and psoriasis.

In this study, we conducted a comprehensive analysis of three distinct research studies to consolidate data and examine current trends in skin disease diagnosis and genetic marker mapping. The findings highlight the immense potential of AI in predicting skin conditions and facilitating early intervention. Consequently, the application of skinomics, microarray technology, and AI techniques has significantly enhanced the prognosis of skin diseases, fostering more accurate diagnostics and treatment strategies. This underscores the pivotal role of AI-driven advancements in improving skin health outcomes

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