Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Machine Learning Informed Diagnosis for Congenital Heart Disease in Large Claims Data Source
15
Zitationen
11
Autoren
2023
Jahr
Abstract
This study shows that a tedious and time-consuming clinical inspection for CHD patient identification can be replaced by an extremely efficient ML algorithm in large claims database. Our findings demonstrate that ML methods can be used to automate complicated algorithms to identify patients with complex diseases.
Ähnliche Arbeiten
"Why Should I Trust You?"
2016 · 14.204 Zit.
A Comprehensive Survey on Graph Neural Networks
2020 · 8.582 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.095 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.463 Zit.
Artificial intelligence in healthcare: past, present and future
2017 · 4.382 Zit.