The Potential of Gemini and GPTs for Structured Report Generation based on Free-Text F-FDG PET/CT Breast Cancer Reports.

Journal: Academic radiology

PMID: 39245597

Abstract

RATIONALE AND OBJECTIVE: To compare the performance of large language model (LLM) based Gemini and Generative Pre-trained Transformers (GPTs) in data mining and generating structured reports based on free-text PET/CT reports for breast cancer after user-defined tasks.

Authors

Kun Chen

Department of Anesthesiology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China.
Wengui Xu

Department of Molecular Image and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Xiaofeng Li

Department of Otorhinolaryngology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University, Shanghai 200233, China.

Keywords

Adult Breast Neoplasms Data Mining Female Fluorodeoxyglucose F18 Humans Middle Aged Natural Language Processing Positron Emission Tomography Computed Tomography Radiology Information Systems Radiopharmaceuticals Retrospective Studies

External Resources

View on PubMed Access via DOI PubMed (39245597)

The Potential of Gemini and GPTs for Structured Report Generation based on Free-Text F-FDG PET/CT Breast Cancer Reports.

Abstract

Authors

Keywords

External Resources

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