{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T13:57:45Z","timestamp":1788184665894,"version":"build-2803163510"},"reference-count":36,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T00:00:00Z","timestamp":1716163200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Life"],"abstract":"<jats:p>The role of artificial intelligence (AI) in healthcare is evolving, offering promising avenues for enhancing clinical decision making and patient management. Limited knowledge about lipedema often leads to patients being frequently misdiagnosed with conditions like lymphedema or obesity rather than correctly identifying lipedema. Furthermore, patients with lipedema often present with intricate and extensive medical histories, resulting in significant time consumption during consultations. AI could, therefore, improve the management of these patients. This research investigates the utilization of OpenAI\u2019s Generative Pre-Trained Transformer 4 (GPT-4), a sophisticated large language model (LLM), as an assistant in consultations for lipedema patients. Six simulated scenarios were designed to mirror typical patient consultations commonly encountered in a lipedema clinic. GPT-4 was tasked with conducting patient interviews to gather medical histories, presenting its findings, making preliminary diagnoses, and recommending further diagnostic and therapeutic actions. Advanced prompt engineering techniques were employed to refine the efficacy, relevance, and accuracy of GPT-4\u2019s responses. A panel of experts in lipedema treatment, using a Likert Scale, evaluated GPT-4\u2019s responses across six key criteria. Scoring ranged from 1 (lowest) to 5 (highest), with GPT-4 achieving an average score of 4.24, indicating good reliability and applicability in a clinical setting. This study is one of the initial forays into applying large language models like GPT-4 in specific clinical scenarios, such as lipedema consultations. It demonstrates the potential of AI in supporting clinical practices and emphasizes the continuing importance of human expertise in the medical field, despite ongoing technological advancements.<\/jats:p>","DOI":"10.3390\/life14050646","type":"journal-article","created":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T11:06:41Z","timestamp":1716203201000},"page":"646","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Integrating AI in Lipedema Management: Assessing the Efficacy of GPT-4 as a Consultation Assistant"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1985-8368","authenticated-orcid":false,"given":"Tim","family":"Leypold","sequence":"first","affiliation":[{"name":"Department of Plastic Surgery, Hand Surgery\u2013Burn Center, University Hospital RWTH Aachen, Pauwelsstra\u00dfe 30, 52074 Aachen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1946-879X","authenticated-orcid":false,"given":"Lara F.","family":"Lingens","sequence":"additional","affiliation":[{"name":"Department of Plastic Surgery, Hand Surgery\u2013Burn Center, University Hospital RWTH Aachen, Pauwelsstra\u00dfe 30, 52074 Aachen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0179-1962","authenticated-orcid":false,"given":"Justus P.","family":"Beier","sequence":"additional","affiliation":[{"name":"Department of Plastic Surgery, Hand Surgery\u2013Burn Center, University Hospital RWTH Aachen, Pauwelsstra\u00dfe 30, 52074 Aachen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anja M.","family":"Boos","sequence":"additional","affiliation":[{"name":"Department of Plastic Surgery, Hand Surgery\u2013Burn Center, University Hospital RWTH Aachen, Pauwelsstra\u00dfe 30, 52074 Aachen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e52865","DOI":"10.2196\/52865","article-title":"The Impact of Multimodal Large Language Models on Health Care\u2019s Future","volume":"25","year":"2023","journal-title":"J. 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