Therapeutic application of machine learning in psoriasis: A Prisma systematic review

Abstract

Dermatology, being a predominantly visual‐based diagnostic field, has found itself to be at the epitome of artificial intelligence (AI)‐based advances. Machine learning (ML), a subset of AI, goes a step further by recognizing patterns from data and teaches machines to automatically learn tasks. Although artificial intelligence in dermatology is mostly developed in melanoma and skin cancer diagnosis, advances in AI and ML have gone far ahead and found its application in ulcer assessment, psoriasis, atopic dermatitis, onychomycosis, etc. This article is focused on the application of ML in the therapeutic aspect of psoriasis.

Artificial intelligence in psoriasis: Where we are and where we are going

“…AI has been applied to various aspects of psoriasis, including disease diagnosis, treatment decision‐making and management (Table 1). These applications have the potential to revolutionize the way in which psoriasis is managed 14,15 …”

“…Due to its complex pathogenesis and varied clinical features, the development of accurate diagnosis and effective treatments for psoriasis has been a significant challenge 13 . Given that the disease is primarily evaluated and managed via visual inspection and has a high prevalence, AI can play a crucial role in tasks such as those described above 14,15 …”

Drug repurposing in psoriasis, performed by reversal of disease-associated gene expression profiles

“…Many different techniques have also been used for drug repurposing for psoriasis. Advances in AI and ML have been witnessed for applications in psoriasis and other related conditions [13] . A recent Ensembl machine learning (ML) based study was published to predict the unknow drug-drug interactions (DDIs) for psoriasis [14] .…”

Artificial intelligence in melanoma: A systematic review

“…According to the data presented by the World Health Organization and the International Agency for Research on Cancer, the global incidence of melanoma is growing steadily 10 . As technologies developed, the application of artificial intelligence and artificial intelligence's new advances in melanoma, machine learning, and deep learning has aroused much concern in the community 11 . The role of dermatologists in developing artificial intelligence for the assessment of skin cancer was systematically reviewed 12 .…”

“…10 As technologies developed, the application of artificial intelligence and artificial intelligence's new advances in melanoma, machine learning, and deep learning has aroused much concern in the community. 11 The role of dermatologists in developing artificial intelligence for the assessment of skin cancer was systematically reviewed. 12 Machine…”