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Artificial Intelligence Bringing Newer Paradigms in the Diagnosis, Treatment, and Management of Psoriasis

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Abstract

Purpose of Review

As we know, psoriasis is the most prevalent chronic inflammatory skin condition due to aberrant immune response which is characterized by clearly demarcated red or pink thick raised skin plaques sometimes covered with dry thin silvery white scales, formed due to the cytokine-driven hyperproliferation of epidermal keratinocytes. The abnormal functioning of immune-inflammatory pathways can cause various systemic conditions including cardiovascular diseases, chronic renal disease, and metabolic syndrome.

Recent Findings

In comparison to other dermatological conditions, psoriasis has greater impact on the mental health of patients leading to increased risk of psychiatric comorbidities such as depression and anxiety. The Articial intellingence could automate the analysis and provide contextual relevance, enhance clinical reliability, assist the clinicians in communicating objectively, minimize human fatigue related errors, decrease mortality rates, save medical expenditures and help in easy and early diagnosis of diseases including psoriasis.

Summary

Therefore, development of better approaches for the diagnosis of psoriasis and determination of its classification type and severity are necessary for disease control and management and are the need of the hour. The artificial intelligence (AI) applications in medicine and healthcare are recently emerging due to advanced computing technologies and availability of abundant data on a variety of diseases including psoriasis. Hence, AI will certainly be a boon for the early detection and management of psoriasis patients necessitating further research in this area.

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Data Availability

This is to declare that all the data has been shared in the manuscript and there is no associated data.

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Acknowledgements

The authors are thankful to their respective institutes for providing the requisite platform to write this manuscript. The authors wish to thank Dr. Tej Khaket for reviewing their manuscript.

Funding

There was no funding received for the said work.

Author information

Authors and Affiliations

  1. Department of Bio-Sciences and Technology, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, 133207, Haryana, India

    Ravi Kant Sharma

  2. Dr. Harvansh Singh Judge Institute of Dental Sciences & Hospital, Punjab University, Chandigarh, India

    Ravi Kant Sharma & Simranjit Singh

  3. Department of Health and Planning, ESI Hospital, Tahliwal, Una, H.P., India

    Manu Rashmi Sharma

  4. Department of Dermatology, MMIMSR, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, 133207, Haryana, India

    Aneet Mahendra

  5. Department of Molecular Medicine, Central University of Punjab, Bathinda, Punjab, India

    Ujjawal Sharma

  6. University Centre for Research and Development, University Institute of Biotechnology, Chandigarh University, Mohali, Punjab, India

    Seema Ramniwas

  7. Department of Biotechnology, Amity University, Sector 82 A IT City Rd, Block D, Sahibzada Ajit Singh, Nagar, Punjab, 140306, India

    Anil Kumar Sharma

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  1. Ravi Kant Sharma
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Contributions

RKS and MRS: Conceptualization, Data curation, writing original draft, Reviewing and Editing. AM, US, SS, SR: Data curation, analysis, Figure preparation, Reviewing and Editing; AKS: Conceptualization, Reviewing and Editing, Visualization, and Supervision.

Corresponding author

Correspondence to Anil Kumar Sharma.

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Sharma, R.K., Sharma, M.R., Mahendra, A. et al. Artificial Intelligence Bringing Newer Paradigms in the Diagnosis, Treatment, and Management of Psoriasis. Curr Derm Rep 12, 314–320 (2023). https://doi.org/10.1007/s13671-023-00408-6

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