Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Entering the new digital era of intensive care medicine: an overview of interdisciplinary approaches to use artificial intelligence for patients’ benefit
6
Zitationen
4
Autoren
2022
Jahr
Abstract
The idea of implementing artificial intelligence in medicine is as old as artificial intelligence itself. So far, technical difficulties have prevented the integration of artificial intelligence in day-to-day healthcare. During the coronavirus disease 2019 (COVID-19) pandemic, a substantial amount of funding went into projects to research and implement artificial intelligence in healthcare. So far, artificial intelligence-based tools have had little impact in the fight against COVID-19. The reasons for the lack of success are complex. With advancing digitalisation, new data-based developed methods and research are finding their way into intensive care medicine. Data scientists and medical professionals, representing two different worlds, are slowly uniting. These two highly specialised fields do not yet speak a uniform language. Each field has its own interests and objectives. We took this idea as a starting point for this technical guide and aim to provide a deeper understanding of the terminology, applications, opportunities and risks of such applications for physicians. The most important terms in the field of machine learning are defined within a medical context to assure that the same language is spoken. The future of artificial intelligence applications will largely depend on the ability of artificial intelligence experts and physicians to cooperate in order to release the true power of artificial intelligence. Large research consortia, covering both technical and medical expertise, will grow because of growing demand in the future.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.357 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.221 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.640 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 · 5.482 Zit.