{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T01:45:25Z","timestamp":1792028725573,"version":"4.4.0"},"reference-count":98,"publisher":"Georg Thieme Verlag KG","issue":"04","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nuklearmedizin"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This study evaluated ChatGPT (GPT-5.2) for drafting a review paper on deep learning in dopamine transporter (DAT)-SPECT with [\u00b9\u00b2\u00b3I]ioflupane.<\/jats:p>\n                  <jats:p>The review workflow consisted of 3 steps: (i) literature search, (ii) generation of structured summaries with 24 predefined fields for each publication, and (iii) drafting a review paper based on the structured summaries across all publications. A detailed prompt for ChatGPT was iteratively designed for each step with ChatGPT support. A manual literature search was independently performed by an expert in DAT-SPECT and deep learning. ChatGPT-generated structured summaries were manually fact-checked against the full publications and corrected where necessary. The review draft generated by ChatGPT was checked against the corrected summaries.<\/jats:p>\n                  <jats:p>When prompted to compile an exhaustive list of publications, ChatGPT cited 13 papers, whereas the manual search identified 70 relevant publications, 67 of which were included. Corrections to ChatGPT-generated structured summaries were required in 27 cases (40.3%), affecting one or two of the 24 predefined fields, while no changes were necessary in 40 publications (59.7%). Most corrections could likely have been avoided by more precise prompting. All numerical information (dataset sizes, train-test splits, performance metrics) was correct. The review draft (~950 words) generated by ChatGPT was content-wise meaningful and accurate, but contained referencing errors, including incorrect citations, missing references, and citations of non-existent publications.<\/jats:p>\n                  <jats:p>ChatGPT is a highly effective tool for drafting review manuscripts in nuclear medicine imaging, but its limitations in literature retrieval and referencing require careful expert supervision.<\/jats:p>","DOI":"10.1055\/a-2890-8325","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T22:50:21Z","timestamp":1782341421000},"page":"255-264","source":"Crossref","is-referenced-by-count":2,"title":["On the utility of ChatGPT in conducting a literature review on deep learning for dopamine transporter SPECT with [\u00b9\u00b2\u00b3I]ioflupane"],"prefix":"10.1055","volume":"65","author":[{"given":"Henning","family":"Boecker","sequence":"first","affiliation":[{"name":"German Center for Neurodegenerative 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Germany","place":["Hamburg"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ivayla Ilieva","family":"Apostolova","sequence":"additional","affiliation":[{"name":"University Medical Center Hamburg-Eppendorf, Germany","place":["Hamburg"],"department":["Department of Diagnostic and Interventional Radiology and Nuclear Medicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roland","family":"Opfer","sequence":"additional","affiliation":[{"name":"jung diagnostics GmbH, Germany","place":["Hamburg"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Susanne","family":"Klutmann","sequence":"additional","affiliation":[{"name":"University Medical Center Hamburg-Eppendorf, Germany","place":["Hamburg"],"department":["Department of Diagnostic and Interventional Radiology and Nuclear Medicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rickmer","family":"Braren","sequence":"additional","affiliation":[{"name":"University Medical 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