Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Developing a Knowledge Base from Oncological Patients’ Neurosurgical Operations Data
0
Zitationen
2
Autoren
2024
Jahr
Abstract
A case of working with real data from a medical institution to support diagnostic decisions is considered. Various approaches to solving the classification problem are discussed. The paper describes methods of separating patient data into positive and negative outcomes following operations and providing clear, interpretable, explainable, and trustworthy results. Examples of the work of the proposed JSM method on data are given with a demonstration of the result obtained.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.231 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.084 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.444 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 · 5.423 Zit.