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Radboud University review artificial intelligence applications
Review Artificial Intelligence Applications, supplied by Radboud University, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/artificial+intelligence/applications+artificial+intelligence+review/pm42250455-15-0-41
Average 86 stars, based on 1 article reviews

review artificial intelligence applications - by Bioz Stars, 2026-11

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Article Title: Sleep characteristics across the lifespan in 1.1 million people from the Netherlands, United Kingdom and United States: a systematic review and meta-analysis.
Article Snippet: 35School for Psychology and Artificial Intelligence, Radboud University, Nijmegen, the Netherlands.

Article Title: 34 th European Congress of Pathology - Abstracts
Article Snippet: OFP-10-002 Association of metastatic pattern in breast cancer with tumour type and patient specific factors: a nationwide autopsy study using artificial intelligence F. Kazemzadeh* , A. Snoek, Q. Voorham, N. Hugen, M.G.H. van Oijen, I. Nagtegaal *Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands; Department of Medical Oncology, Amsterdam University Medical Center, University of Amsterdam, The Netherlands, Cancer Center Amsterdam, Therapy Program, The Netherlands Background & objectives: Heterogeneity of metastatic pattern of breast cancer hampers treatment decisions.

Article Title: Sonosensitive Phase-Changeable Nanoparticle Mediated Enhanced Chemotherapy in Prostate Cancer by Low-Intensity Focused Ultrasound
Article Snippet: Scientists from Radboud University Medical Center reported a comprehensive international verification of artificial intelligence (AI) technology for the diagnosis and rating of prostate cancer through research [ ].

Article Title: Weakly Supervised Classification of Mohs Surgical Sections Using Artificial Intelligence.
Article Snippet: Basal cell carcinoma (BCC) is the most frequently diagnosed form of skin cancer, and its incidence continues to rise, particularly among older individuals.. This trend puts a significant strain on health care systems, especially in terms of histopathologic diagnostics required for Mohs micrographic surgery (MMS), which is used to treat BCC in sensitive locations to minimize tissue loss.. This study aims to address the challenges in BCC detection within MMS whole-slide images by developing and evaluating a deep learning model that bridges weakly supervised learning with interpretable segmentation-based methods through attention maps.

Article Title: Automated detection and numbering of primary and permanent teeth in digital impressions of children using artificial intelligence.
Article Snippet: primary and permanent teeth in digital impressions of children using artificial intelligence Niels van Nistelrooija,b,*, Haline Cunha de Medeiros Maiac,d,*, Lingyun Caoc, Shankeeth Vinayahalingama, Bas Loomansc , Maximiliano Sergio Cencic, Fausto Medeiros Mendesc,d aDepartment of Oral and Maxillofacial Surgery, Radboud University Medical Center, Nijmegen, the Netherlands bDepartment of Oral and Maxillofacial Surgery, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany cDepartment of Dentistry, Radboud University Medical Center, Nijmegen, the Netherlands dDepartment of Pediatric Dentistry, School of Dentistry, University of São Paulo, São Paulo, Brazil *Niels van Nistelrooij and Haline Cunha de Medeiros Maia have contributed equally to this article

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Article Title: Artificial intelligence for breast cancer detection in mammography and digital breast tomosynthesis: State of the art.
Article Snippet: .. Artificial Intelligence for Breast Cancer Detection in Mammography and Digital Breast Tomosynthesis: state of the art Special Issue: “Precision Medicine in Breast Cancer: from Biological Imaging to Artificial Intelligence” Ioannis Sechopoulos, PhDa,b*, Jonas Teuwen, PhDa,c, Ritse Mann, MD, PhDa,d aDepartment of Radiology, Nuclear Medicine and Anatomy, Radboud University Medical Center, Geert Grooteplein 10, 6525 GA, Nijmegen, the Netherlands bDutch Expert Centre for Screening (LRCB), Wijchenseweg 101, 6538 SW, Nijmegen, the Netherlands cDepartment of Radiation Oncology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, the Netherlands dDepartment of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, the Netherlands *Corresponding author: Ioannis Sechopoulos P.O. ..

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Article Title: Artificial Intelligence for breast cancer detection: Technology, challenges, and prospects.
Article Snippet: .. Review Artificial Intelligence for breast cancer detection: Technology, challenges, and prospects Oliver Díaz a,b, Alejandro Rodríguez-Ruíz c, Ioannis Sechopoulos d,e,f,* a Artificial Intelligence in Medicine Laboratory, Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Spain b Computer Vision Center, Barcelona, Spain c ScreenPoint Medical, Nijmegen, the Netherlands d Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands e Dutch Expert Centre for Screening (LRCB), Nijmegen, the Netherlands f Technical Medicine Center, University of Twente, Enschede, the Netherlands A R T I C L E I N F O Keywords: Breast cancer Breast imaging Artificial intelligence Mammography Screening A B S T R A C T Purpose: This review provides an overview of the current state of artificial intelligence (AI) technology for automated detection of breast cancer in digital mammography (DM) and digital breast tomosynthesis (DBT). ..

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