Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting.
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| Title: | Inferring cancer disease response from radiology reports using large language models with data augmentation and prompting. |
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| Authors: | Tan RSYC; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.; Duke-NUS Medical School, Singapore., Lin Q; Department of Computer Science, National University of Singapore, Singapore., Low GH; Division of Medical Oncology, National Cancer Centre Singapore, Singapore., Lin R; Department of Computer Science, National University of Singapore, Singapore., Goh TC; Institute of Systems Science, National University of Singapore, Singapore., Chang CCE; Institute of Systems Science, National University of Singapore, Singapore., Lee FF; Institute of Systems Science, National University of Singapore, Singapore., Chan WY; Institute of Systems Science, National University of Singapore, Singapore., Tan WC; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.; Duke-NUS Medical School, Singapore., Tey HJ; Division of Medical Oncology, National Cancer Centre Singapore, Singapore., Leong FL; Division of Medical Oncology, National Cancer Centre Singapore, Singapore., Tan HQ; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Nei WL; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Chay WY; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.; Duke-NUS Medical School, Singapore., Tai DWM; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.; Duke-NUS Medical School, Singapore., Lai GGY; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.; Duke-NUS Medical School, Singapore., Cheng LT; Duke-NUS Medical School, Singapore.; Department of Diagnostic Radiology, Singapore General Hospital, Singapore., Wong FY; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Chua MCH; Yong Loo Lin School of Medicine, National University of Singapore, Singapore., Chua MLK; Duke-NUS Medical School, Singapore.; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore.; Data and Computational Science Core, National Cancer Centre Singapore, Singapore., Tan DSW; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.; Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre Singapore, Singapore., Thng CH; Duke-NUS Medical School, Singapore.; Division of Oncologic Imaging, National Cancer Centre Singapore, Singapore., Tan IBH; Division of Medical Oncology, National Cancer Centre Singapore, Singapore.; Duke-NUS Medical School, Singapore.; Data and Computational Science Core, National Cancer Centre Singapore, Singapore., Ng HT; Department of Computer Science, National University of Singapore, Singapore. |
| Source: | Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2023 Sep 25; Vol. 30 (10), pp. 1657-1664. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9430800 Publication Model: Print Cited Medium: Internet ISSN: 1527-974X (Electronic) Linking ISSN: 10675027 NLM ISO Abbreviation: J Am Med Inform Assoc Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1527-974X |
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| DOI: | 10.1093/jamia/ocad133 |
