Artificial intelligence in diagnosis and monitoring of atopic dermatitis: From pixels to predictions

Abstract

In any ailment, the identification of the symptoms, detection, and diagnosis plays a pivotal role in treatment and therapy. However, certain diseases share similar symptoms, lacking signature key indicators, which can lead to fallacious or incorrect inferences. Skin disorders, such as pruritus, dermatitis, eczema, psoriasis, and ichthyosis, all present similar symptoms, which confound clinicians. One such commonly misunderstood condition is atopic dermatitis (AD), a chronic inflammatory skin condition characterized by its relapsing nature, which heightens the importance of diagnosis and disease monitoring for effective management. Recent strides in artificial intelligence (AI) have opened avenues for precise diagnosis and continuous monitoring of AD. This review explores and evaluates current applications of AI in the diagnosis and monitoring of individuals with AD emphasizing the need to address challenges and collaborate across intra-, inter-, trans-, and multi-disciplinary domains to maximize the benefits of AI in enhancing the precision of AD diagnosis, ultimately leading to improved patient care and satisfaction through technologically-driven biomedical tools in customized healthcare.