126 citations
- University of GenevaCH14 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Geneva CollegeUS5 papers
- InsermFR5 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR4 papers
- Université Paris-SaclayFR3 papers
- University Hospital of BernCH3 papers
- University Medical Center GroningenNL3 papers
- University Medical Center UtrechtNL3 papers
- University of British ColumbiaCA3 papers
- University of Southern DenmarkDK3 papers
- Utrecht UniversityNL3 papers
29 papers
Who Is in the Room? Stakeholder Perspectives on AI Recording in Pediatric Emergency Care
Alexandre De Masi, Sergio Manzano, Johan N. Siebert +1
Artificial intelligence systems that record voice and video during pediatric emergencies are emerging as human-computer interaction (HCI) technologies with direct implications for…
Position-Sensitive Silicon Photomultiplier Array with Enhanced Position Reconstruction by means of a Deep Neural Network
Cyril Alispach, Fabio Acerbi, Hossein Arabi +4
Single-photon sensitive detectors like Silicon Photomultipliers are widely used in many medical imaging applications. By using detectors with position resolutions, it is possible t…
Automated segmentation of pediatric neuroblastoma on multi-modal MRI: Results of the SPPIN challenge at MICCAI 2023
M. A. D. Buser, D. C. Simons, M. Fitski +27
Surgery plays an important role within the treatment for neuroblastoma, a common pediatric cancer. This requires careful planning, often via magnetic resonance imaging (MRI)-based…
AI-Augmented Thyroid Scintigraphy for Robust Classification of Disease
Maziar Sabouri, Ghasem Hajianfar, Alireza Rafiei Sardouei +11
Thyroid scintigraphy is vital for diagnosing thyroid disorders, yet deep learning (DL) models in this domain often struggle with limited, imbalanced datasets. This study investigat…
DOME Registry: Implementing community-wide recommendations for reporting supervised machine learning in biology
Omar Abdelghani Attafi, Damiano Clementel, Konstantinos Kyritsis +17
Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The DOME recommendations aim to enhance the validation and reproducibility of ML resea…
Thyroidiomics: An Automated Pipeline for Segmentation and Classification of Thyroid Pathologies from Scintigraphy Images
Maziar Sabouri, Shadab Ahamed, Azin Asadzadeh +13
The objective of this study was to develop an automated pipeline that enhances thyroid disease classification using thyroid scintigraphy images, aiming to decrease assessment time…