Harry Collin, Kandice Keogh, Marnique Basto, Stacy Loeb, Matthew J Roberts
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引用次数: 0
Abstract
Background/objectives: Patients often face uncertainty about what they should know after prostate cancer diagnosis. Web-based information is common but is at risk of being of poor quality or readability.
Subjects/methods: We used ChatGPT, a freely available Artificial intelligence (AI) platform, to generate enquiries about prostate cancer that a newly diagnosed patient might ask and compared to Google search trends. Then, we evaluated ChatGPT responses to these questions for clinical appropriateness and quality using standardised tools.
Results: ChatGPT generates broad and representative questions, and provides understandable, clinically sound advice.
Conclusions: AI can guide and empower patients after prostate cancer diagnosis through education. However, the limitations of the ChatGPT language-model must not be ignored and require further evaluation and optimisation in the healthcare field.
期刊介绍：
Prostate Cancer and Prostatic Diseases covers all aspects of prostatic diseases, in particular prostate cancer, the subject of intensive basic and clinical research world-wide. The journal also reports on exciting new developments being made in diagnosis, surgery, radiotherapy, drug discovery and medical management.
Prostate Cancer and Prostatic Diseases is of interest to surgeons, oncologists and clinicians treating patients and to those involved in research into diseases of the prostate. The journal covers the three main areas - prostate cancer, male LUTS and prostatitis.
Prostate Cancer and Prostatic Diseases publishes original research articles, reviews, topical comment and critical appraisals of scientific meetings and the latest books. The journal also contains a calendar of forthcoming scientific meetings. The Editors and a distinguished Editorial Board ensure that submitted articles receive fast and efficient attention and are refereed to the highest possible scientific standard. A fast track system is available for topical articles of particular significance.
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