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Updated: Apr 13, 2026

The Goeckerman Regimen for the Treatment of Moderate to Severe Psoriasis
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Advancing Psoriasis Care through Artificial Intelligence: A Comprehensive Review.

Payton Smith1, Chandler E Johnson1, Kathryn Haran1

  • 1Department of Dermatology, University of California San Francisco, San Francisco, CA, USA.

Current Dermatology Reports
|September 20, 2024
PubMed
Summary
This summary is machine-generated.

Machine learning (ML), a form of artificial intelligence (AI), is transforming psoriasis care by enhancing diagnosis, severity assessment, and personalized treatment strategies. Dermatologist oversight is crucial for integrating AI effectively into patient care.

Keywords:
DermatologyMachine learningPrecision medicinePsoriasis

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Area of Science:

  • Dermatology
  • Artificial Intelligence
  • Machine Learning

Background:

  • Machine learning (ML), a subset of artificial intelligence (AI), has advanced fields like image classification and speech recognition.
  • Integrating ML into clinical medicine, especially dermatology, represents a significant improvement in healthcare delivery.

Purpose of the Study:

  • To review the impact of ML on psoriasis care, focusing on diagnosis, severity assessment, biomarker identification, precision medicine, and education.
  • To explore how ML applications can improve patient outcomes, particularly in underserved areas.

Main Methods:

  • Review of current literature on ML applications in dermatology concerning psoriasis.
  • Analysis of ML's role in diagnosing psoriasis from clinical and dermoscopic images.
  • Examination of ML for quantifying psoriasis severity and identifying biomarkers.

Main Results:

  • ML aids in psoriasis diagnosis, severity quantification, and biomarker discovery.
  • ML enhances precision medicine approaches and AI-driven educational strategies for psoriasis management.
  • AI integration promises improved patient outcomes, especially where specialist care is limited.

Conclusions:

  • The synergy between AI and human expertise is key to advancing dermatological treatments.
  • ML offers potential for more accessible and precise personalized psoriasis care.
  • Dermatologist supervision is essential to ensure ML's effective and ethical application in patient care.