Isabella J Tan, Olivia M Katamanin, Rachel K Greene, Mohammad Jafferany
{"title":"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。","authors":"Isabella J Tan, Olivia M Katamanin, Rachel K Greene, Mohammad Jafferany","doi":"10.1111/srt.70044","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":21746,"journal":{"name":"Skin Research and Technology","volume":"30 9","pages":"e70044"},"PeriodicalIF":2.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11359090/pdf/","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.\",\"authors\":\"Isabella J Tan, Olivia M Katamanin, Rachel K Greene, Mohammad Jafferany\",\"doi\":\"10.1111/srt.70044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Materials and methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":21746,\"journal\":{\"name\":\"Skin Research and Technology\",\"volume\":\"30 9\",\"pages\":\"e70044\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11359090/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Skin Research and Technology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/srt.70044\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"DERMATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Skin Research and Technology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/srt.70044","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DERMATOLOGY","Score":null,"Total":0}
Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.
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.
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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