Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Enhancing Oncological Surveillance Through Large Language Model-Assisted Analysis: A Comparative Study of GPT-4 and Gemini in Evaluating Oncological Issues From Serial Abdominal CT Scan Reports
11
Zitationen
9
Autoren
2024
Jahr
Abstract
This study demonstrated the potential of LLM-assisted analysis of serial radiology reports in enhancing oncological surveillance, using a carefully engineered prompt. GPT-4 showed superior performance compared to Gemini in matching corresponding findings, identifying tumor-related findings, and accurately determining tumor status.
Ähnliche Arbeiten
New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)
2008 · 28.913 Zit.
TNM Classification of Malignant Tumours
1987 · 16.123 Zit.
A survey on deep learning in medical image analysis
2017 · 13.595 Zit.
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
2011 · 10.773 Zit.
The American Joint Committee on Cancer: the 7th Edition of the AJCC Cancer Staging Manual and the Future of TNM
2010 · 9.111 Zit.