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Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data

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Produktnummer: 18a000554b95d04e23b13f55eaf9bf1e41
Themengebiete: analysis of biomedical data classification methods computer networks computer science computer systems computer vision correlation analysis deep learning deep learning models for medical applications evolutionary algorithms
Veröffentlichungsdatum: 21.09.2021
EAN: 9783030874438
Sprache: Englisch
Seitenzahl: 129
Produktart: Kartoniert / Broschiert
Herausgeber: Cardoso, Jaime Hajij, Mustafa Henriques Abreu, Pedro Rahul, Paul Reyes, Mauricio Thakur, Lokendra Zamzmi, Ghada
Verlag: Springer International Publishing
Untertitel: 4th International Workshop, iMIMIC 2021, and 1st International Workshop, TDA4MedicalData 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings
Produktinformationen "Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data"
This book constitutes the refereed joint proceedings of the 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, and the First International Workshop on Topological Data Analysis and Its Applications for Medical Data, TDA4MedicalData 2021, held on September 27, 2021, in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021.The 7 full papers presented at iMIMIC 2021 and 5 full papers held at TDA4MedicalData 2021 were carefully reviewed and selected from 12 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. TDA4MedicalData is focusing on using TDA techniques to enhance the performance, generalizability, efficiency, and explainability of the current methods applied to medical data.

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