Dermatology Unit, Azienda Unità Sanitaria Locale-IRCCS di Reggio Emilia, Reggio Emilia, Italy.
University of Modena and Reggio Emilia, Modena, Italy.
J Eur Acad Dermatol Venereol. 2024 Dec;38(12):2225-2234. doi: 10.1111/jdv.20286. Epub 2024 Aug 16.
Natural Language Processing (NLP) is a field of both computational linguistics and artificial intelligence (AI) dedicated to analysis and interpretation of human language.
This systematic review aims at exploring all the possible applications of NLP techniques in the dermatological setting.
Extensive search on 'natural language processing' and 'dermatology' was performed on MEDLINE and Scopus electronic databases. Only journal articles with full text electronically available and English translation were considered. The PICO (Population, Intervention or exposure, Comparison, Outcome) algorithm was applied to our study protocol.
Natural Language Processing (NLP) techniques have been utilized across various dermatological domains, including atopic dermatitis, acne/rosacea, skin infections, non-melanoma skin cancers (NMSCs), melanoma and skincare. There is versatility of NLP in data extraction from diverse sources such as electronic health records (EHRs), social media platforms and online forums. We found extensive utilization of NLP techniques across diverse dermatological domains, showcasing its potential in extracting valuable insights from various sources and informing diagnosis, treatment optimization, patient preferences and unmet needs in dermatological research and clinical practice.
While NLP shows promise in enhancing dermatological research and clinical practice, challenges such as data quality, ambiguity, lack of standardization and privacy concerns necessitate careful consideration. Collaborative efforts between dermatologists, data scientists and ethicists are essential for addressing these challenges and maximizing the potential of NLP in dermatology.
自然语言处理（NLP）是计算语言学和人工智能（AI）的一个领域，致力于分析和解释人类语言。
本系统评价旨在探索 NLP 技术在皮肤科领域的所有可能应用。
在 MEDLINE 和 Scopus 电子数据库上广泛搜索“自然语言处理”和“皮肤病学”。仅考虑具有全文电子可用和英文翻译的期刊文章。我们的研究方案应用了 PICO（人群、干预或暴露、比较、结局）算法。
自然语言处理（NLP）技术已应用于各种皮肤科领域，包括特应性皮炎、痤疮/酒渣鼻、皮肤感染、非黑素瘤皮肤癌（NMSC）、黑素瘤和皮肤护理。NLP 在从电子健康记录（EHR）、社交媒体平台和在线论坛等各种来源提取数据方面具有多功能性。我们发现 NLP 技术在各种皮肤科领域得到了广泛应用，展示了其从各种来源提取有价值见解的潜力，并为皮肤科研究和临床实践中的诊断、治疗优化、患者偏好和未满足的需求提供信息。
虽然 NLP 有望增强皮肤科的研究和临床实践，但数据质量、歧义、缺乏标准化和隐私问题等挑战需要谨慎考虑。皮肤科医生、数据科学家和伦理学家之间的合作对于应对这些挑战和最大限度地发挥 NLP 在皮肤科中的潜力至关重要。
