01850nas a2200217   4500000000100000008004100001260004600042653002800088653001100116653002000127653002000147100001300167700001000180700001500190245011300205856014000318300001200458490000700470520113000477022002501607       2025                            d  bOvid Technologies (Wolters Kluwer Health)10aArtificial Intelligence10aWounds10aDiagnostic test10alanguage models1 aNelson S1 aLay B1 aJohnson AR00aArtificial Intelligence in Skin and Wound Care: Enhancing Diagnosis and Treatment With Large Language Models  uhttps://journals.lww.com/aswcjournal/_layouts/15/oaks.journals/downloadpdf.aspx?trckng_src_pg=ArticleViewer&an=00129334-202510000-00003  a457-4610 v383 a<p>Artificial intelligence (AI) is revolutionizing the landscape of skin and wound care by improving diagnostic accuracy, treatment effectiveness, and patient outcomes. Artificial intelligence–driven tools, including machine learning models and large language models (LLMs), enhance the precision of wound assessments, facilitate early infection detection, and streamline clinical workflows. In addition, these tools may aid in patient symptom reporting, bridging the communication gap between patients and health care providers. Current AI applications include image recognition for wound classification, patient-facing symptom-checking chatbots, and personalized treatment recommendations. The integration of AI technologies not only supports better clinical decision-making but also empowers patients through improved access, engagement, and education. These tools are currently aimed at supporting clinical decision-making, not replacing clinicians. Moving forward, the expansion of AI capabilities in skin and wound care holds great promise, driving cost-effective, scalable, and equitable health care solutions.</p>
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