{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T15:46:42Z","timestamp":1790610402728,"version":"4.1.0"},"reference-count":22,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"10","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"\n \n \n \u00bb Generative artificial intelligence (AI), a rapidly evolving field, has the potential to revolutionize orthopedic care by enhancing diagnostic accuracy, treatment planning, and patient management through data-driven insights and personalized strategies.<\/jats:p>\n <\/jats:list-item>\n \n \u00bb Unlike traditional AI, generative AI has the potential to generate relevant information for orthopaedic surgeons when instructed through prompts, automating tasks such as literature reviews, streamlining workflows, predicting health outcomes, and improving patient interactions.<\/jats:p>\n <\/jats:list-item>\n \n \u00bb Prompt engineering is essential for crafting effective prompts for large language models (LLMs), ensuring accurate and reliable AI-generated outputs, and promoting ethical decision-making in clinical settings.<\/jats:p>\n <\/jats:list-item>\n \n \u00bb Orthopaedic surgeons can choose between various prompt types\u2013including open-ended, focused, and choice-based prompts\u2013to tailor AI responses for specific clinical tasks to enhance the precision and utility of generated information.<\/jats:p>\n <\/jats:list-item>\n \n \u00bb Understanding the limitations of LLMs, such as token limits, context windows, and hallucinations, is crucial for orthopaedic surgeons to effectively use generative AI while addressing ethical concerns related to bias, privacy, and accountability.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n 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