Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Lior Ness"'
Publikováno v:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 ISBN: 9783030597245
MICCAI (6)
MICCAI (6)
Breast screening is an effective method to identify breast cancer in asymptomatic women; however, not all exams are read by radiologists specialized in breast imaging, and missed cancers are a reality. Deep learning provides a valuable tool to suppor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6af56f995640f06a2b4e3d021ca4182e
https://doi.org/10.1007/978-3-030-59725-2_24
https://doi.org/10.1007/978-3-030-59725-2_24
Publikováno v:
Interpretable and Annotation-Efficient Learning for Medical Image Computing ISBN: 9783030611651
iMIMIC/MIL3iD/LABELS@MICCAI
iMIMIC/MIL3iD/LABELS@MICCAI
Cancer prediction models, which deeply impact human lives, must provide explanations for their predictions. We study a simple extension of a cancer mammogram classifier, trained with image-level annotations, to facilitate the built-in generation of p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b87d631b55ae4b000dc69c00de0a7ab2
https://doi.org/10.1007/978-3-030-61166-8_4
https://doi.org/10.1007/978-3-030-61166-8_4
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030322250
MICCAI (6)
MICCAI (6)
When reading imaging studies, radiologists often compare the acquired images to one or more prior studies of the patient. Machine learning algorithms that assist in identifying abnormalities in medical images usually do not analyze prior images. This
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cfb82bf642c2953e5155a7ba3e2b8a51
https://doi.org/10.1007/978-3-030-32226-7_79
https://doi.org/10.1007/978-3-030-32226-7_79
Autor:
Sara Abu-Ghanem, Lior Ness, Ophir Handzel, Miri Ben-Artzi-Blima, Karin Fait-Ghelbendorf, Mordechai Himmelfarb
Publikováno v:
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery. 273(2)
Hearing loss is widespread among the elderly. One of the main obstacles to rehabilitation is identifying individuals with potentially correctable hearing loss. Smartphone-based hearing tests can be administered at home, thus greatly facilitating acce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::679c08991f6315a29395bec84872ff8b
https://pubmed.ncbi.nlm.nih.gov/25655259
https://pubmed.ncbi.nlm.nih.gov/25655259
