TY - BOOK ID - 126324064 TI - Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging AU - Wesarg, Stefan AU - Puyol Anton, Esther AU - Baxter, John S H AU - Erdt, Marius AU - Drechsler, Klaus AU - Oyarzun Laura, Cristina AU - Freiman, Moti AU - Chen, Yufei AU - Rekik, Islem AU - Feragen, Aasa AU - King, Andrew P AU - Cheplygina, Veronika AU - Ganz-Benjaminsen, Melani AU - Ferrante, Enzo AU - Glocker, Ben AU - Moyer, Daniel AU - Petersen, Eikel AU - Eagleson, Roy AU - SpringerLink (Online service) PY - 2023 SN - 9783031452499 3031452496 3031452488 PB - Cham Springer Nature Switzerland :Imprint: Springer DB - UniCat KW - Computer vision. KW - Machine learning. KW - Artificial intelligence. KW - Computer networks. KW - Information technology KW - Computer Vision. KW - Machine Learning. KW - Artificial Intelligence. KW - Computer Communication Networks. KW - Computer Application in Administrative Data Processing. KW - Management. KW - Artificial intelligence KW - Diagnostic imaging KW - Medical applications KW - Data processing UR - https://www.unicat.be/uniCat?func=search&query=sysid:126324064 AB - This book constitutes the refereed proceedings of the 12th International Workshop on Clinical Image-Based Procedures, CLIP 2023, the First MICCAI Workshop on Fairness of AI in Medical Imaging, FAIMI 2023, held in conjunction with MICCAI 2023, in October 2023, and the Second MICCAI Workshop on the Ethical and Philosophical Issues in Medical Imaging, EPIMI 2023. CLIP 2023 accepted 5 full papers and 3 short papers form 8 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice. For FAIMI 2023, 19 full papers have been accepted from 20 submissions. They focus on creating awareness about potential fairness issues that can emerge in the context of machine learning. And for EPIMI 2023, 2 papers have been accepted from 5 submissions. They investigate questions that underlie medical imaging research at the most fundamental level. . ER -