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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Künstliche Intelligenz und maschinelles Lernen in der onkologischen Bildgebung.
Artificial intelligence and machine learning in oncologic imaging.
Pathologe 41, 649-658 (2020)
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.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Computer-assisted Image Processing ; Deep Learning ; Diagnostic Imaging ; Machine Learning ; Neural Networks (computer)
ISSN (print) / ISBN
0172-8113
e-ISSN
1432-1963
Zeitschrift
Pathologe, Der
Quellenangaben
Band: 41,
Heft: 6,
Seiten: 649-658
Verlag
Springer
Begutachtungsstatus
Peer reviewed