Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence and the Risk for Intuition Decline in Clinical Medicine
6
Zitationen
2
Autoren
2022
Jahr
Abstract
Abstract Artificial intelligence (AI) is revolutionizing big data analytics. In this issue of The American Journal of Gastroenterology , Ahn et al. introduce the AI-cirrhosis-electrocardiogram score that can grade the electrophysiologic cardiac changes present in patients with cirrhosis. Apart from showing excellent accuracy to identify cirrhosis, the AI-cirrhosis-electrocardiogram algorithm identified a biological gradient and signal reversibility after transplantation. Clinical applicability needs to be determined. Some concerns inherent to the use of AI are discussed, including the need to verify that the quality of data used for machine training is optimal. The black box nature of AI-identified associations is discussed, along with the lack of pathophysiologic coherence allowing intuitive medical reasoning.
Ähnliche Arbeiten
"Why Should I Trust You?"
2016 · 14.391 Zit.
A Comprehensive Survey on Graph Neural Networks
2020 · 8.721 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.261 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.695 Zit.
Artificial intelligence in healthcare: past, present and future
2017 · 4.436 Zit.