Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence in Decision-Making for Colorectal Cancer Treatment Strategy: An Observational Study of Implementing Watson for Oncology in a 250-Case Cohort
33
Zitationen
15
Autoren
2021
Jahr
Abstract
Clinical recommendations made by WFO and the cancer team were highly matched for colorectal cancer. Patient age, cancer stage, and the consideration of previous therapy details had a significant influence on concordance. Addressing these perspectives will facilitate the use of the cancer decision-support systems to help oncologists achieve the promise of precision medicine.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.393 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.259 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.688 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.502 Zit.