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E-book
Author MLMECH (Workshop) (1st : 2019 : Shenzhen Shi, China)

Title Machine learning and medical engineering for cardiovascular health and intravascular imaging and computer assisted stenting : first International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings / Hongen Liao, Simone Balocco, Guijin Wang et al. (Eds.)
Published Cham, Switzerland : Springer, 2019

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Description 1 online resource (xvii, 212 pages) : illustrations (some color)
Series Lecture notes in computer science ; 11794
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics
Lecture notes in computer science ; 11794.
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics.
Contents Intro; Additional Workshop Editors; MLMECH-MICCAI 2019 Preface; Organization; Joint MICCAI-Workshops on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting (MICCAI CVII-STENT 2019); Organization; Contents; Proceedings of the Machine Learning and Medical Engineering for Cardiovascular Health; Arrhythmia Classification with Attention-Based Res-BiLSTM-Net; Abstract; 1 Introduction; 2 Methods; 2.1 Attention-Based Resnet; 2.2 Attention-Based BiLSTM; 3 Experiment; 3.1 Dataset Description; 3.2 Experiment Setup; 3.3 Evaluation Metrics
3.4 Model Performance on Test Dataset4 Conclusion and Discussion; Acknowledgment; References; A Multi-label Learning Method to Detect Arrhythmia Based on 12-Lead ECGs; Abstract; 1 Introduction; 2 Dataset and the Proposed Method; 2.1 Database; 2.2 Data Preprocessing; 2.3 Two Losses; 2.4 SE-ResNet; 2.5 Test Protocol; 3 Experimental Results; 4 Conclusions; Acknowledgements; References; An Ensemble Neural Network for Multi-label Classification of Electrocardiogram; 1 Introduction; 2 Model Architecture; 2.1 Sequence Generation Module; 2.2 Multi-task Module; 2.3 Implementation Details; 3 Experiment
3.1 Dataset and Evaluation Metric3.2 Results; 4 Conclusion and Future Work; References; Automatic Diagnosis with 12-Lead ECG Signals; 1 Introduction; 2 Dataset Description; 3 Methods; 3.1 Data Pre-processing; 3.2 Feature Engineering; 3.3 Deep Learning Models; 3.4 Overall Framework; 3.5 Training; 4 Competition Results; 5 Conclusion; References; Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks; 1 Introduction; 2 Dataset; 3 The Architecture; 3.1 Heuristic Features; 3.2 Global Pooling Layer; 4 Details of Learning
4.1 Data Preprocessing4.2 Data Augmentation; 4.3 Optimization; 5 Results; 6 Conclusion; References; Transfer Learning for Electrocardiogram Classification Under Small Dataset; Abstract; 1 Introduction; 2 Methodology; 2.1 Deep Residual Network for Electrocardiogram Classification; 2.2 Network Training; 2.3 Evaluation Metric; 3 Dataset; 4 Results; 5 Conclusion; Acknowledgements; References; Multi-label Classification of Abnormalities in 12-Lead ECG Using 1D CNN and LSTM; Abstract; 1 Introduction; 2 Methods; 2.1 Data Description; 2.2 Architectures; 2.3 Training; 3 Results
4 Conclusion and DiscussionAcknowledgments; References; An Approach to Predict Multiple Cardiac Diseases; Abstract; 1 Introduction; 1.1 Background; 1.2 Project Introduction; 2 Methods; 2.1 QRS Detection and Median Complex; 2.2 Detection of Morphology Abnormalities; 2.3 Detection of Rhythm Abnormalities; 2.4 CNN Model; 2.5 Machine Learning Model; 3 Results; Acknowledgement; References; A 12-Lead ECG Arrhythmia Classification Method Based on 1D Densely Connected CNN; Abstract; 1 Introduction; 2 Methods; 2.1 Data Augmentation; 2.2 Data Segmentation; 2.3 Model Architecture and Training
Summary This book constitutes the refereed proceedings of the First International Workshop on Machine Learning and Medical Engineering for Cardiovasvular Healthcare, MLMECH 2019, and the International Joint Workshops on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For MLMECH 2019, 16 papers were accepted for publication from a total of 21 submissions. They focus on machine learning techniques and analyzing of ECG data in the diagnosis of heart diseases. CVII-STENT 2019 accepted all 8 submissiones for publication. They contain technological and scientific research concerning endovascular procedures
Notes International conference proceedings
Includes author index
Online resource; title from PDF title page (SpringerLink, viewed October 16, 2019)
Subject Medical informatics -- Congresses
Biomedical engineering -- Congresses
Radiography, Medical -- Congresses
Biomedical engineering
Medical informatics
Radiography, Medical
Genre/Form Electronic books
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Form Electronic book
Author Liao, Hongen, editor.
Balocco, Simone, editor.
Wang, Guijin (Writer on iImage processing), editor.
CVII-STENT (Workshop) (8th : 2019 : Shenzhen Shi, China), jointly held conference.
International Conference on Medical Image Computing and Computer-Assisted Intervention (22nd : 2019 : Shenzhen Shi, China), jointly held conference.
ISBN 9783030333270
3030333272