Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Amir L. Rifi"'
Autor:
Camille Raets, Chaimae El Aisati, Amir L. Rifi, Mark De Ridder, Koen Putman, Johan De Mey, Alexandra Sermeus, Kurt Barbe
Publikováno v:
IEEE Open Journal of Instrumentation and Measurement, Vol 3, Pp 1-12 (2024)
The growing popularity of artificial intelligence (AI) has increased its widespread adoption in medicine. However, the relationship between AI and medical experts’ opinions remains elusive. This study investigated the consistency between Random For
Externí odkaz:
https://doaj.org/article/f80974049da94341a3da4aaa8357ef29
Radiomic features are typically used in machine learning models and are proven to generate reliable results when predicting tumor grade and responses to treatment. However, the inherent non-biological-interpretability of the radiomic features strongl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7156e2ee10f423f8e84ea9825e0eea00
https://hdl.handle.net/20.500.14017/e84f7601-55ad-48d0-8d4f-f5aff1a8f52a
https://hdl.handle.net/20.500.14017/e84f7601-55ad-48d0-8d4f-f5aff1a8f52a
Radiomics has the potential of characterizing the tumor phenotype hidden in medical images, allowing us to get more out of medical images than the eyes can see and liberating us from only using lesion size as a tumor response criterion. The extracted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d89d62b91c14a2ad49caa4d03763a37
https://biblio.vub.ac.be/vubir/unraveling-the-biological-meaning-of-radiomic-features(32637e89-caff-425e-991a-a60e30d2b050).html
https://biblio.vub.ac.be/vubir/unraveling-the-biological-meaning-of-radiomic-features(32637e89-caff-425e-991a-a60e30d2b050).html