Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Evaluating the potential of ChatGPT for patient identification in clinical breast cancer trials
0
Zitationen
11
Autoren
2025
Jahr
Abstract
While model performance was limited by simplified input data and a small single-center cohort, the results suggest that ChatGPT-4.0, in its current form, is not yet suitable as a stand-alone tool for patient identification in clinical breast cancer trials. To ensure accurate and efficient recruitment, the involvement of a multiprofessional team remains essential. Ongoing model refinement and access to larger, more detailed datasets may enhance the future utility of AI systems in clinical trial screening.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.250 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.109 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.482 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 · 5.434 Zit.