Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Accuracy and Reproducibility of ChatGPT Responses to Breast Cancer Tumor Board Patients
3
Zitationen
18
Autoren
2025
Jahr
Abstract
Since this promising clinical decision-making support tool is widely used currently by physicians worldwide, it is important for the user to understand its limitations as currently constructed when responding to multidisciplinary breast cancer patients, and for researchers in the field to continue improving its ability with contemporary, accurate and complete breast cancer information. As currently constructed, ChatGPT is not engineered to generate identical outputs to the same input and was less likely to correctly interpret and recommend treatments for complex breast cancer patients.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.214 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.071 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.429 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.418 Zit.
Autoren
Institutionen
- Guangdong Academy of Medical Sciences(CN)
- Guangdong Provincial People's Hospital(CN)
- Cancer Care Northwest(US)
- Northwestern University(US)
- The University of Texas Medical Branch at Galveston(US)
- The University of Texas MD Anderson Cancer Center(US)
- Georgetown University(US)
- Georgetown University Medical Center(US)
- MedStar Health(US)
- MedStar Georgetown University Hospital(US)
- Washington University in St. Louis(US)
- Clinica Universidad de Navarra(ES)
- Fred Hutch Cancer Center(US)
- Pittsburg State University(US)
- UPMC Hillman Cancer Center(US)
- University of Pittsburgh(US)
- Dana-Farber Cancer Institute(US)
- University of California, San Francisco(US)
- UCSF Helen Diller Family Comprehensive Cancer Center(US)