Dermatophytic infections of the skin and appendages are a common occurrence. The pathogenesis involves complex interplay of agent (dermatophytes), host (inherent host defense and host immune response) and the environment. Infection management has become an important public health issue, due to increased incidence of recurrent, recalcitrant or extensive infections. Recent years have seen a significant rise in incidence of chronic infections which have been difficult to treat. In this review, we review the literature on management of dermatophytoses and bridge the gap in therapeutic recommendations.

Artificial intelligence (AI), a major frontier in the field of medical research, can potentially lead to a paradigm shift in clinical practice. A type of artificial intelligence system known as convolutional neural network points to the possible utility of deep learning in dermatopathology. Though pathology has been traditionally restricted to microscopes and glass slides, recent advancement in digital pathological imaging has led to a transition making it a potential branch for the implementation of artificial intelligence. The current application of artificial intelligence in dermatopathology is to complement the diagnosis and requires a well-trained dermatopathologist’s guidance for better designing and development of deep learning algorithms. Here we review the recent advances of artificial intelligence in dermatopathology, its applications in disease diagnosis and in research, along with its limitations and future potential.

Introduction: Ever evolving research in medical field has reached an exciting stage with advent of newer technologies. With the introduction of digital microscopy, pathology has transitioned to become more digitally oriented speciality. The potential of artificial intelligence (AI) in dermatopathology is to aid the diagnosis, and it requires dermatopathologists' guidance for efficient functioning of artificial intelligence.Method: Comprehensive literature search was performed using electronic online databases “PubMed” and “Google Scholar.” Articles published in English language were considered for the review.Results: Convolutional neural network, a type of deep neural network, is considered as an ideal tool in image recognition, processing, classification, and segmentation. Implementation of AI in tumor pathology is involved in the diagnosis, grading, staging, and prognostic prediction as well as in identification of genetic or pathological features. In this review, we attempt to discuss the use of AI in dermatopathology, the attitude of patients and clinicians, its challenges, limitation, and potential opportunities in future implementation.

Dermatology journal, dermatology online, dermatology, skin diseases, skin articles