[Artificial intelligence and machine learning in oncologic imaging].
Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung.
Computer-assisted image processing
Deep learning
Diagnostic imaging
Machine learning
Neural networks (computer)
Journal
Der Pathologe
ISSN: 1432-1963
Titre abrégé: Pathologe
Pays: Germany
ID NLM: 8006541
Informations de publication
Date de publication:
Nov 2020
Nov 2020
Historique:
pubmed:
15
10
2020
medline:
8
1
2021
entrez:
14
10
2020
Statut:
ppublish
Résumé
Machine learning (ML) is entering many areas of society, including medicine. This transformation has the potential to drastically change medicine and medical practice. These aspects become particularly clear when considering the different stages of oncologic patient care and the involved interdisciplinary and intermodality interactions. In recent publications, computers-in collaboration with humans or alone-have been outperforming humans regarding tumor identification, tumor classification, estimating prognoses, and evaluation of treatments. In addition, ML algorithms, e.g., artificial neural networks (ANNs), which constitute the drivers behind many of the latest achievements in ML, can deliver this level of performance in a reproducible, fast, and inexpensive manner. In the future, artificial intelligence applications will become an integral part of the medical profession and offer advantages for oncologic diagnostics and treatment.
Identifiants
pubmed: 33052431
doi: 10.1007/s00292-020-00827-3
pii: 10.1007/s00292-020-00827-3
doi:
Types de publication
Journal Article
Langues
ger
Sous-ensembles de citation
IM