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{ "item_title" : "Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support", "item_author" : [" Kenji Suzuki", "Mauricio Reyes", "Tanveer Syeda-Mahmood "], "item_description" : "Second 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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/03/033/849/3030338495_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support|Kenji Suzuki

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support : Second International Worksh

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Overview

Second 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.

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Details

  • ISBN-13: 9783030338497
  • ISBN-10: 3030338495
  • Publisher: Springer
  • Publish Date: October 2019
  • Dimensions: 9.21 x 6.14 x 0.23 inches
  • Shipping Weight: 0.37 pounds
  • Page Count: 93

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