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<p>Oral Lichen Planus (OLP) is a common chronic inflammatory disorder with a complex etiology and potential for malignant transformation, posing substantial challenges for clinical diagnosis and management. Conventional diagnostic approaches often depend on clinical experience and subjective assessment, which limits their accuracy and efficiency. Recent advances in artificial intelligence (AI) have introduced novel paradigms for investigating OLP characteristics. This review examines current applications, progress, challenges, and future directions of AI in OLP diagnosis and classification, prediction of disease progression and prognosis, and analysis of molecular features. Through a critical evaluation of existing research, AI demonstrates considerable potential to improve diagnostic objectivity, accelerate clinical decision-making, and reveal underlying disease mechanisms, thereby supporting the development of precision medicine for OLP.</p>

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Artificial intelligence in the study of oral lichen planus characteristics: a review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月4日

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  • Huishun Yang,
  • Ge Li,
  • Changbin Zhao

摘要

Oral Lichen Planus (OLP) is a common chronic inflammatory disorder with a complex etiology and potential for malignant transformation, posing substantial challenges for clinical diagnosis and management. Conventional diagnostic approaches often depend on clinical experience and subjective assessment, which limits their accuracy and efficiency. Recent advances in artificial intelligence (AI) have introduced novel paradigms for investigating OLP characteristics. This review examines current applications, progress, challenges, and future directions of AI in OLP diagnosis and classification, prediction of disease progression and prognosis, and analysis of molecular features. Through a critical evaluation of existing research, AI demonstrates considerable potential to improve diagnostic objectivity, accelerate clinical decision-making, and reveal underlying disease mechanisms, thereby supporting the development of precision medicine for OLP.