Purpose of review: Machine learning (ML), a subset of artificial intelligence (AI), has been vital in advancing tasks such as image classification and speech recognition. Its integration into clinical medicine, particularly dermatology, offers a significant leap in healthcare delivery.

Recent findings: This review examines the impact of ML on psoriasis-a condition heavily reliant on visual assessments for diagnosis and treatment. The review highlights five areas where ML is reshaping psoriasis care: diagnosis of psoriasis through clinical and dermoscopic images, skin severity quantification, psoriasis biomarker identification, precision medicine enhancement, and AI-driven education strategies. These advancements promise to improve patient outcomes, especially in regions lacking specialist care. However, the success of AI in dermatology hinges on dermatologists' oversight to ensure that ML's potential is fully realized in patient care, preserving the essential human element in medicine.

Summary: This collaboration between AI and human expertise could define the future of dermatological treatments, making personalized care more accessible and precise.

Keywords: Dermatology; Machine learning; Precision medicine; Psoriasis.

回顾目的: 机器学习（ML）是人工智能（AI）的一个子集，在图像分类和语音识别等任务中发挥了重要作用。将其融入临床医学，特别是皮肤科，为医疗保健的提供带来了重大飞跃。

近期发现: 本次回顾探讨了机器学习对银屑病的影响——这是一种严重依赖于视觉评估进行诊断和治疗的情况。该回顾强调了五个领域，其中机器学习正在重塑银屑病护理：通过临床和皮肤镜图像诊断银屑病、皮肤严重程度量化、银屑病生物标志物识别、精确医学改进以及人工智能驱动的教育策略。这些进展有望改善患者结果，在缺乏专科护理的地区尤为显著。然而，AI在皮肤病学中的成功取决于皮肤科医生的监督，以确保机器学习的潜力完全实现于患者的护理中，并保留医学中必不可少的人类因素。

摘要: 人工智能与人类专业知识之间的合作可能定义了未来皮肤疾病治疗的方向，使个性化医疗更加普及和精确。

关键词: 皮肤病学；机器学习；精准医学；银屑病。