Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.

IF 2 4区 医学 Q3 DERMATOLOGY
Isabella J Tan, Olivia M Katamanin, Rachel K Greene, Mohammad Jafferany
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引用次数: 0

Abstract

Background: This report evaluates the potential of artificial intelligence (AI) in psychodermatology, emphasizing its ability to enhance diagnostic accuracy, treatment efficacy, and personalized care. Psychodermatology, which explores the connection between mental health and skin disorders, stands to benefit from AI's advanced data analysis and pattern recognition capabilities.

Materials and methods: A literature search was conducted on PubMed and Google Scholar, spanning from 2004 to 2024, following PRISMA guidelines. Studies included demonstrated AI's effectiveness in predicting treatment outcomes for body dysmorphic disorder, identifying biomarkers in psoriasis and anxiety disorders, and refining therapeutic strategies.

Results: The review identified several studies highlighting AI's role in improving treatment outcomes and diagnostic accuracy in psychodermatology. AI was effective in predicting outcomes for body dysmorphic disorder and identifying biomarkers related to psoriasis and anxiety disorders. However, challenges such as limited dermatologist knowledge, integration difficulties, and ethical concerns regarding patient privacy were noted.

Conclusion: AI holds significant promise for advancing psychodermatology by improving diagnostic precision, treatment effectiveness, and personalized care. Nonetheless, realizing this potential requires large-scale clinical validation, enhanced dataset diversity, and robust ethical frameworks. Future research should focus on these areas, with interdisciplinary collaboration essential for overcoming current challenges and optimizing patient care in psychodermatology.

人工智能在精神皮肤病学中的应用:临床实践中的应用和影响简要报告。
背景:本报告评估了人工智能(AI)在精神皮肤病学中的潜力,强调了人工智能在提高诊断准确性、治疗效果和个性化护理方面的能力。精神皮肤病学探索心理健康与皮肤疾病之间的联系,将受益于人工智能先进的数据分析和模式识别能力:根据 PRISMA 指南,我们在 PubMed 和 Google Scholar 上进行了文献检索,时间跨度为 2004 年至 2024 年。所纳入的研究证明了人工智能在预测身体畸形障碍的治疗效果、确定银屑病和焦虑症的生物标志物以及完善治疗策略方面的有效性:综述确定了几项研究,强调了人工智能在改善治疗效果和提高精神皮肤病诊断准确性方面的作用。人工智能能有效预测身体畸形障碍的治疗效果,并确定与银屑病和焦虑症相关的生物标志物。然而,我们也注意到了一些挑战,如皮肤科医生知识有限、整合困难以及有关患者隐私的伦理问题:通过提高诊断精确度、治疗效果和个性化护理,人工智能有望推动精神皮肤病学的发展。然而,实现这一潜力需要大规模的临床验证、增强数据集的多样性以及健全的伦理框架。未来的研究应重点关注这些领域,跨学科合作对于克服当前的挑战和优化精神皮肤病学的患者护理至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Skin Research and Technology
Skin Research and Technology 医学-皮肤病学
CiteScore
3.30
自引率
9.10%
发文量
95
审稿时长
6-12 weeks
期刊介绍: Skin Research and Technology is a clinically-oriented journal on biophysical methods and imaging techniques and how they are used in dermatology, cosmetology and plastic surgery for noninvasive quantification of skin structure and functions. Papers are invited on the development and validation of methods and their application in the characterization of diseased, abnormal and normal skin. Topics include blood flow, colorimetry, thermography, evaporimetry, epidermal humidity, desquamation, profilometry, skin mechanics, epiluminiscence microscopy, high-frequency ultrasonography, confocal microscopy, digital imaging, image analysis and computerized evaluation and magnetic resonance. Noninvasive biochemical methods (such as lipids, keratin and tissue water) and the instrumental evaluation of cytological and histological samples are also covered. The journal has a wide scope and aims to link scientists, clinical researchers and technicians through original articles, communications, editorials and commentaries, letters, reviews, announcements and news. Contributions should be clear, experimentally sound and novel.
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