LEADER 05533nam 22007215 450 001 9910349269203321 005 20210130071607.0 010 $a3-030-33850-9 024 7 $a10.1007/978-3-030-33850-3 035 $a(CKB)4100000009678320 035 $a(MiAaPQ)EBC5968218 035 $a(DE-He213)978-3-030-33850-3 035 $a(PPN)253256879 035 $a(EXLCZ)994100000009678320 100 $a20191024d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInterpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support$b[electronic resource] $eSecond International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings /$fedited by Kenji Suzuki, Mauricio Reyes, Tanveer Syeda-Mahmood, Ender Konukoglu, Ben Glocker, Roland Wiest, Yaniv Gur, Hayit Greenspan, Anant Madabhushi 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (xvi, 93 pages) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v11797 300 $aIncludes index. 311 $a3-030-33849-5 327 $aSecond International Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2019) -- Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification -- UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics -- Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis -- Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection -- Guideline-based Additive Explanation for Computer-Aided Diagnosis of Lung Nodules -- Deep neural network or dermatologist? -- Towards Interpretability of Segmentation Networks by analyzing DeepDreams -- 9th International Workshop on Multimodal Learning for Clinical Decision Support (ML-CDS 2019) -- Towards Automatic Diagnosis from Multi-modal Medical Data -- Deep Learning based Multi-Modal Registration for Retinal Imaging -- Automated Enriched Medical Concept Generation for Chest X-ray Images. 330 $aThis book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. . 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v11797 606 $aArtificial intelligence 606 $aMathematical logic 606 $aHealth informatics 606 $aOptical data processing 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23060 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 615 0$aArtificial intelligence. 615 0$aMathematical logic. 615 0$aHealth informatics. 615 0$aOptical data processing. 615 14$aArtificial Intelligence. 615 24$aMathematical Logic and Formal Languages. 615 24$aHealth Informatics. 615 24$aImage Processing and Computer Vision. 676 $a616.07540285 702 $aSuzuki$b Kenji$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aReyes$b Mauricio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSyeda-Mahmood$b Tanveer$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKonukoglu$b Ender$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGlocker$b Ben$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWiest$b Roland$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGur$b Yaniv$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGreenspan$b Hayit$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMadabhushi$b Anant$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910349269203321 996 $aInterpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support$92535216 997 $aUNINA