%{search_type} search results

• Effects of stimuli intensity and frequency on auditory P50 na N100 sensory gating / Gaëlle Spielmann Moura, Yolanda Triñanes-Pego, and Maria T. Carrillo-de-la-Peña
• On buildng a memory evolutive system for applicatin to learning and cognition modeling / Julio de Lima do Rego Monteiro [and others]
• Agent-based cognitive model for human resources competence management / Stefan Oliveira and João Carlos Gluz
• Neural accumulator models of decision making in eye movements / Vassilis Cutsuridis
• On building meaning : a biologically-inspired experiment on symbol-based communication / Angelo Loula [and others]
• Perception-action learning as an epistemologically-consistent model for self-updating cognitive representation / David Windridge and Josef Kittler
• Detection of auditory cortex activity by fMRI using a dependent component analysis / Carlos A. Estombelo-Montesco [and others]
• Brain-computer interface using wavelet transformation and naïve Bayes classsifier / Thiago Bassani and Julio Cesar Nievola
• Neuromorphic systems : past, present, and future / Leslie S. Smith
• Genetic algorithm applied to hierarchically coupled associative memories / Rogério Martins Gomes, Antônio Pádua Braga, and Henrique E. Borges
• Vector quantization of speech frames based on self-organizing maps / Flávio Olmos Simões [and others]
• The use of Bayesian networks for heart beat classification / Lorena Sophia Campos de Oliveira, Rodrigo Varejão Andreão, and Mário Sarcinelli-Filho
• A histogram based method for multiclass classification using SVMs / Sandro Tomassoni Coelho and Carlos Alberto Ynoguti
• Models of consciousness / Ron Chrisley and Rob Clowes
• A functional approach to emotion in autonomous systems / Ricardo Sanz [and others]
• A robot architecture based on higher order perception loop / Antonio Chella
• The consciousness circuit : an approach to the hard problem / Sulamita Frohlich and Carlos A. Franco
• Computational consciousness : building a self-preserving organism / Allan Kardec Barros
• The hippocampal system as the cortical resource manager : a model connecting psychology, anatomy, and physiology / L. Andrew Coward
• Cognitive measure on different profiles / Marilda Spindola [and others].

• Effects of stimuli intensity and frequency on auditory P50 na N100 sensory gating / Gae⁺{136}lle Spielmann Moura, Yolanda Trin⁺ёanes-Pego, and Maria T. Carrillo-de-la-Pen⁺ёa
• On buildng a memory evolutive system for applicatin to learning and cognition modeling / Julio de Lima do Rego Monteiro [and others]
• Agent-based cognitive model for human resources competence management / Stefan Oliveira and Joa⁺ёo Carlos Gluz
• Neural accumulator models of decision making in eye movements / Vassilis Cutsuridis
• On building meaning : a biologically-inspired experiment on symbol-based communication / Angelo Loula [and others]
• Perception-action learning as an epistemologically-consistent model for self-updating cognitive representation / David Windridge and Josef Kittler
• Detection of auditory cortex activity by fMRI using a dependent component analysis / Carlos A. Estombelo-Montesco [and others]
• Brain-computer interface using wavelet transformation and nai⁺{136}ve Bayes classsifier / Thiago Bassani and Julio Cesar Nievola
• Neuromorphic systems : past, present, and future / Leslie S. Smith
• Genetic algorithm applied to hierarchically coupled associative memories / Rogério Martins Gomes, Antônio Pádua Braga, and Henrique E. Borges
• Vector quantization of speech frames based on self-organizing maps / Flávio Olmos Simo⁺ёes [and others]
• The use of Bayesian networks for heart beat classification / Lorena Sophia Campos de Oliveira, Rodrigo Vareja⁺ёo Andrea⁺ёo, and Mário Sarcinelli-Filho
• A histogram based method for multiclass classification using SVMs / Sandro Tomassoni Coelho and Carlos Alberto Ynoguti
• Models of consciousness / Ron Chrisley and Rob Clowes
• A functional approach to emotion in autonomous systems / Ricardo Sanz [and others]
• A robot architecture based on higher order perception loop / Antonio Chella
• The consciousness circuit : an approach to the hard problem / Sulamita Frohlich and Carlos A. Franco
• Computational consciousness : building a self-preserving organism / Allan Kardec Barros
• The hippocampal system as the cortical resource manager : a model connecting psychology, anatomy, and physiology / L. Andrew Coward
• Cognitive measure on different profiles / Marilda Spindola [and others].

Brain Inspired Cognitive Systems 2008 (June 24-27, 2008; Sao Luis, Brazil) brought together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological systems and, specifically, of the brain, and to exploit such knowledge to advance computational methods towards ever higher levels of cognitive competence. This book includes the papers presented at four major symposia: Part I - Cognitive Neuroscience Part II - Biologically Inspired Systems Part III - Neural Computation Part IV - Models of Consciousness.
(source: Nielsen Book Data)

• Technologies for implementing AmIHealth environments.- Frameworks related with AmIHealth environments.- Applied algorithms in e-Health systems.- Interactions within the AmIHealth environments.- Applications and case studies of AmIHealth environments.- Metrics for Health environments.
• (source: Nielsen Book Data)

This book constitutes the refereed conference proceedings of the First International Conference on Ambient Intelligence for Health, AmIHEALTH 2015, held in Puerto Varas, Chile, in December 2015. The 20 revised full papers and 9 short papers were reviewed and selected from 32 submissions and cover topics on technologies for implementing AmIHealth environments; frameworks related with AmIHealth environments; applied algorithms in e-Health systems; interactions within the AmIHealth environments; applications and case studies of AmIHealth environments; and metrics for health environments.
(source: Nielsen Book Data)

• Introduction.- Describing Spatial Position and Orientation.- Robot Kinematics.- Joint Velocities and Jacobi-Matrices.- Navigation and Registration.- Treatment Planning.- Motion Correlation and Tracking.- Motion Prediction.- Motion Replication.- Applications of Surgical Robotics.- Rehabilitation, Neuroprosthetics and Brain-Machine Interfaces.
• (source: Nielsen Book Data)

This book provides a thorough background to the emerging field of medical robotics. It covers the mathematics needed to understand the use of robotic devices in medicine, including but not limited to robot kinematics, hand-eye and robot-world calibration, reconstruction, registration, motion planning, motion prediction, motion correlation, motion replication and motion learning. Additionally, basic methods behind state-of-the art robots like the DaVinci system, the CyberKnife, motorized C-arms and operating microscopes as well as stereotactic frames are presented. The book is a text book for undergraduates in computer science and engineering. The main idea of the book is to motivate the methods in robotics in medical applications rather than industrial applications. The book then follows the standard path for a robotics textbook. It is thus suitable for a first course in robotics for undergraduates. It is the first textbook on medical robotics.
(source: Nielsen Book Data)

• Active learning
• Semi-supervised learning
• Reinforcement learning
• Domain adaptation and transfer learning
• Crowd-sourcing annotations and fusion of labels from different sources
• Data augmentation
• Modelling of label uncertainty
• Visualization and human-computer interaction
• Image description
• Medical imaging-based diagnosis
• Medical signal-based diagnosis
• Medical image reconstruction and model selection using deep learning techniques
• Meta-heuristic techniques for fine-tuning
• Parameter in deep learning-based architectures
• Applications based on deep learning techniques.

This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty. The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.

• Medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain
• Data management, data mining, and knowledge discovery, all of which play a key role in decision making, management of public health, examination of standards, privacy and security issues
• Computer visualization and artificial intelligence for computer aided diagnosis; development of new architectures and applications for health information systems.

This book constitutes the refereed proceedings of the 5th International Conference on Health Information Science, HIS 2016, held in Shanghai, China, in November 2016. The 13 full papers and 9 short papers presented were carefully reviewed and selected from numerous submissions. The scope of the papers includes medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain; data management, data mining, and knowledge discovery, all of which play a key role in decision making, management of public health, examination of standards, privacy and security issues; computer visualization and artificial intelligence for computer aided diagnosis; development of new architectures and applications for health information systems.

• Ecare@Home: A Distributed Research Environment on Semantic Interoperability
• Halmstad Intelligent Home
• Capabilities and Opportunities
• Healthcare needs, company innovations, and research enabling solutions within Embedded Sensor Systems for Health
• A Case-Based Classification for Drivers? Alcohol Detection Using Physiological Signals
• Towards a Probabilistic Method for Longitudinal Monitoring in Health Care
• A Classification Model for Predicting Heart Failure in Cardiac Patients by Using Unstructured Data
• Ins and Outs of Big Data: A Review
• A review of Parkinson?s disease cardinal and dyskinetic motor symptoms assessment methods using sensor systems
• Why Hackers Love eHealth Applications
• Reliable Communication in Health Monitoring Applications11 Security Context Framework for Distributed Healthcare IoT Platform
• BitRun: Gamification of Health Data from Fitbit Activity Trackers
• Smartphone-based Decision Support System for Elimination of Pathology-free Images in Diabetic Retinopathy Screening
• Improving Awareness in Ambient-Assisted Living Systems: Consolidated Data Stream Processing
• Beyond?Happy Apps?: Using the Internet of Things to Support Emotional Health
• TEEM: a Mobile App for Technology-Enhanced Emergency Management
• Perception of Delay in Computer Input Devices Establishing a Baseline for Signal Processing of Motion Sensor Systems
• Telemetry system for diagnosis of Asthma and Chronical Obstructive Pulmonary Disease (COPD)
• Remotely Supporting Patients with Obstructive Sleep Apnea at Home
• An aggregation platform for IoT-based healthcare: illustration for bioimpedancemetry, temperature and fatigue level monitoring.

This book constitutes the proceedings of the Third International Conference on Internet of Things (IoT) Technologies for HealthCare, HealthyIoT 2016, held in Västerås, Sweden, October 18-19, 2016. The conference also included the First Workshop on Emerging eHealth through Internet of Things (EHIoT 2016). IoT as a set of existing and emerging technologies, notions and services provides many solutions to delivery of electronic healthcare, patient care, and medical data management. The 31 revised full papers presented along with 9 short papers were carefully reviewed and selected from 43 submissions in total. The papers cover topics such as healthcare support for the elderly, real-time monitoring systems, security, safety and communication, smart homes and smart caring environments, intelligent data processing and predictive algorithms in e-Health, emerging eHealth IoT applications, signal processing and analysis, and smartphones as a healthy thing.

• The use of technologies in favor of maintaining and improving mental wellbeing
• Building new computing paradigms
• Addressing a multitude of challenges in mental healthcare
• New technologies in psychiatric and psychological domains
• Video and audio technologies and mobile and wearable computing in mental healthcare.

This book constitutes the refereed proceedings of the 5th International Conference on Pervasive Computing Paradigms for Mental Health, MindCare 2015, held in Milan, Italy, in September 2015. The 23 full papers and 6 short papers presented were carefully reviewed and selected from 40 submissions. The papers deal with the use of technologies in favor of maintaining and improving mental wellbeing. They focus on building new computing paradigms and on addressing a multitude of challenges in mental healthcare, for example in psychiatric and psychological domains with emphasis on new technologies, such as video and audio technologies and mobile and wearable computing.

This book contains revised and extended selected papers from two workshops: the 10th International Workshop on Agents Applied in Health Care, A2HC 2017, held at the 16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, held in Sao Paulo, Brazil, in May 2017, and the International Workshop on Agents and Multi-Agent Systems for AAL and e-Health, A-HEALTH 2017, held at the 15th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2017, in Porto, Portugal, in June 2017. The 9 revised full papers were carefully reviewed and selected from 16 submissions. They feature current research topics such as personalised health systems for remote and autonomous tele-assistance, communication and co-operation between distributed intelligent agents to manage patient care, information agents that retrieve medical information from distributed repositories, intelligent and distributed data mining, and multi-agent systems that assist the doctors in the tasks of monitoring, decision support and diagnosis. .
(source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 16th Conference on Artificial Intelligence in Medicine, AIME 2017, held in Vienna, Austria, in June 2017. The 21 revised full and 23 short papers presented were carefully reviewed and selected from 113 submissions. The papers are organized in the following topical sections: ontologies and knowledge representation; Bayesian methods; temporal methods; natural language processing; health care processes; and machine learning, and a section with demo papers. .
(source: Nielsen Book Data)

• Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017:
• Simultaneous Multiple Surface Segmentation Using Deep Learning / Abhay Shah, Michael D. Abramoff, Xiaodong Wu
• A Deep Residual Inception Network for HEp-2 Cell Classification / Yuexiang Li, Linlin Shen
• Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures / Roger Trullo, Caroline Petitjean, Dong Nie, Dinggang Shen, Su Ruan
• Accelerated Magnetic Resonance Imaging by Adversarial Neural Network / Ohad Shitrit, Tammy Riklin Raviv
• Left Atrium Segmentation in CT Volumes with Fully Convolutional Networks / Honghui Liu, Jianjiang Feng, Zishun Feng, Jiwen Lu, Jie Zhou
• 3D Randomized Connection Network with Graph-Based Inference / Siqi Bao, Pei Wang, Albert C. S. Chung
• Adversarial Training and Dilated Convolutions for Brain MRI Segmentation / Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim
• CNNs Enable Accurate and Fast Segmentation of Drusen in Optical Coherence Tomography / Shekoufeh Gorgi Zadeh, Maximilian W. M. Wintergerst, Vitalis Wiens, Sarah Thiele, Frank G. Holz, Robert P. Finger et al.
• Region-Aware Deep Localization Framework for Cervical Vertebrae in X-Ray Images / S. M. Masudur Rahman Al Arif, Karen Knapp, Greg Slabaugh
• Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images / Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta
• Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks / Sangheum Hwang, Sunggyun Park
• Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms / Fatemeh Taheri Dezaki, Neeraj Dhungel, Amir H. Abdi, Christina Luong, Teresa Tsang, John Jue et al.
• Computationally Efficient Cardiac Views Projection Using 3D Convolutional Neural Networks / Matthieu Le, Jesse Lieman-Sifry, Felix Lau, Sean Sall, Albert Hsiao, Daniel Golden
• Non-rigid Craniofacial 2D-3D Registration Using CNN-Based Regression / Yuru Pei, Yungeng Zhang, Haifang Qin, Gengyu Ma, Yuke Guo, Tianmin Xu et al.
• A Deep Level Set Method for Image Segmentation / Min Tang, Sepehr Valipour, Zichen Zhang, Dana Cobzas, Martin Jagersand
• Context-Based Normalization of Histological Stains Using Deep Convolutional Features / D. Bug, S. Schneider, A. Grote, E. Oswald, F. Feuerhake, J. Schüler et al.
• Transitioning Between Convolutional and Fully Connected Layers in Neural Networks / Shazia Akbar, Mohammad Peikari, Sherine Salama, Sharon Nofech-Mozes, Anne Martel
• Quantifying the Impact of Type 2 Diabetes on Brain Perfusion Using Deep Neural Networks / Behrouz Saghafi, Prabhat Garg, Benjamin C. Wagner, S. Carrie Smith, Jianzhao Xu, Ananth J. Madhuranthakam et al.
• Multi-stage Diagnosis of Alzheimer's Disease with Incomplete Multimodal Data via Multi-task Deep Learning / Kim-Han Thung, Pew-Thian Yap, Dinggang Shen
• A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification / William Lotter, Greg Sorensen, David Cox
• Analyzing Microscopic Images of Peripheral Blood Smear Using Deep Learning / Dheeraj Mundhra, Bharath Cheluvaraju, Jaiprasad Rampure, Tathagato Rai Dastidar
• AGNet: Attention-Guided Network for Surgical Tool Presence Detection / Xiaowei Hu, Lequan Yu, Hao Chen, Jing Qin, Pheng-Ann Heng
• Pathological Pulmonary Lobe Segmentation from CT Images Using Progressive Holistically Nested Neural Networks and Random Walker / Kevin George, Adam P. Harrison, Dakai Jin, Ziyue Xu, Daniel J. Mollura
• End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network / Bob D. de Vos, Floris F. Berendsen, Max A. Viergever, Marius Staring, Ivana Išgum
• Stain Colour Normalisation to Improve Mitosis Detection on Breast Histology Images / Azam Hamidinekoo, Reyer Zwiggelaar
• 3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation / Masahiro Oda, Natsuki Shimizu, Holger R. Roth, Ken'ichi Karasawa, Takayuki Kitasaka, Kazunari Misawa et al.
• A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology / Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim
• Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations / Carole H. Sudre, Wenqi Li, Tom Vercauteren, Sebastien Ourselin, M. Jorge Cardoso
• ssEMnet: Serial-Section Electron Microscopy Image Registration Using a Spatial Transformer Network with Learned Features / Inwan Yoo, David G. C. Hildebrand, Willie F. Tobin, Wei-Chung Allen Lee, Won-Ki Jeong
• Fully Convolutional Regression Network for Accurate Detection of Measurement Points / Michal Sofka, Fausto Milletari, Jimmy Jia, Alex Rothberg
• Fast Predictive Simple Geodesic Regression / Zhipeng Ding, Greg Fleishman, Xiao Yang, Paul Thompson, Roland Kwitt, Marc Niethammer et al.
• Learning Spatio-Temporal Aggregation for Fetal Heart Analysis in Ultrasound Video / Arijit Patra, Weilin Huang, J. Alison Noble
• Fast, Simple Calcium Imaging Segmentation with Fully Convolutional Networks / Aleksander Klibisz, Derek Rose, Matthew Eicholtz, Jay Blundon, Stanislav Zakharenko
• Self-supervised Learning for Spinal MRIs / Amir Jamaludin, Timor Kadir, Andrew Zisserman
• Skin Lesion Segmentation via Deep RefineNet / Xinzi He, Zhen Yu, Tianfu Wang, Baiying Lei
• Multi-scale Networks for Segmentation of Brain Magnetic Resonance Images / Jie Wei, Yong Xia
• Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography / Ayelet Akselrod-Ballin, Leonid. Karlinsky, Alon Hazan, Ran Bakalo, Ami Ben Horesh, Yoel Shoshan et al.
• Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections / Adam Porisky, Tom Brosch, Emil Ljungberg, Lisa Y. W. Tang, Youngjin Yoo, Benjamin De Leener et al.
• 7th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017:
• Mapping Multi-Modal Routine Imaging Data to a Single Reference via Multiple Templates / Johannes Hofmanninger, Bjoern Menze, Marc-André Weber, Georg Langs
• Automated Detection of Epileptogenic Cortical Malformations Using Multimodal MRI / Ravnoor S. Gill, Seok-Jun Hong, Fatemeh Fadaie, Benoit Caldairou, Boris Bernhardt, Neda Bernasconi et al.
• Prediction of Amyloidosis from Neuropsychological and MRI Data for Cost Effective Inclusion of Pre-symptomatic Subjects in Clinical Trials / Manon Ansart, Stéphane Epelbaum, Geoffroy Gagliardi, Olivier Colliot, Didier Dormont, Bruno Dubois et al.
• Automated Multimodal Breast CAD Based on Registration of MRI and Two View Mammography / T. Hopp, P. Cotic Smole, N. V. Ruiter
• EMR-Radiological Phenotypes in Diseases of the Optic Nerve and Their Association with Visual Function / Shikha Chaganti, Jamie R. Robinson, Camilo Bermudez, Thomas Lasko, Louise A. Mawn, Bennett A. Landman
• Erratum to: Fast Predictive Simple Geodesic Regression / Zhipeng Ding, Greg Fleishman, Xiao Yang, Paul Thompson, Roland Kwitt, Marc Niethammer et al.

This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
(source: Nielsen Book Data)

• 2.2 Kernel-Radius-Based Feature Extraction Method
• 3 Experiments
• 3.1 Database
• 3.2 The Experimental Results and Discussions
• 4 Conclusion
• References
• Some Directions of Medical Informatics in Russia
• Abstract
• 1 Gelfand's Approach to Medical Informatics
• 1.1 Personal Applicability of the Result
• 1.2 Using the Experience of a Doctor
• 1.3 Proof of the Result
• 2 Medical Information System "Transfusiology"
• 3 Time-Oriented Multi-image Case History
• Way to the "Disease Image" Analysis
• Acknowledgements
• References

• A Computer Simulation Approach to Reduce Appointment Lead-Time in Outpatient Perinatology Department ...
• Abstract
• 1 Introduction
• 2 Related Work
• 3 Modeling the Perinatology Department: A Case Study in a Maternal-Child Hospital
• 4 Conclusions and Future Work
• References
• Engaging Patients, Empowering Doctors in Digitalization of Healthcare
• Abstract
• 1 Introduction
• 2 Methods and Discussion
• 3 Conclusion
• Acknowledgements
• References
• Developing a Tunable Q-Factor Wavelet Transform Based Algorithm for Epileptic EEG Feature Extraction
• Abstract
• 1 Introduction

• 2 Datasets and Methods
• 2.1 Experimental Data
• 2.2 Methodology
• 3 Performance Measurements
• 4 Experimental Results and Discussions
• 5 Conclusions
• References
• Granular Computing Combined with Support Vector Machines for Diagnosing Erythemato-Squamous Diseases
• 1 Introduction
• 2 The Basic Knowledge of GrC and SVM
• 2.1 The Basic Idea of GrC
• 2.2 Support Vector Machines
• 3 GrC and SVM Based Feature Selection Algorithm
• 3.1 Feature search strategies
• 3.2 Search for Best Parameters
• 3.3 GrC Combined SVM Feature Selection Algorithm
• 4 Experiments and Results

• 4.1 The Erythemato-Squamous Diseases Dataset
• 4.2 Experimental Results and Analysis
• 5 Conclusions
• References
• A Semantically-Enabled System for Inflammatory Bowel Diseases
• 1 Introduction
• 2 System
• 3 Semantic Queries
• 4 Experiments
• 4.1 Basic Information
• 4.2 IBD Onset Distribution
• 4.3 Season and Smoking Factors Analysis
• 5 Related Research
• 6 Conclusions
• References
• Early Classification of Multivariate Time Series Based on Piecewise Aggregate Approximation
• Abstract
• 1 Introduction
• 2 Background
• 3 Related Work

This book constitutes the refereed proceedings of the 6th International Conference on Health Information Science, HIS 2017, held in Moscow, Russia, in October 2017. The 11 full papers and 7 short papers presented were carefully reviewed and selected from 44 submissions. The papers feature multidisciplinary research results in health information science and systems that support health information management and health service delivery. They relate to all aspects of the conference scope, such as medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain; data management, data mining, and knowledge discovery, management of publichealth, examination of standards, privacy and security issues; computer visualization and artificial intelligence for computer aided diagnosis; development of new architectures and applications for health information systems.
(source: Nielsen Book Data)

This book constitutes the refereed joint proceedings of the 6th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2017, and the Second International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 6 full papers presented at CVII-STENT 2017 and the 11 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.
(source: Nielsen Book Data)

• Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases.- BigBrain: Automated Cortical Parcellation and Comparison with Existing Brain Atlases.- LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images.- Landmark-based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images.- Inferring Disease Status by non-Parametric Probabilistic Embedding.- A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images.- Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study.- Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker.- Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation.- Automatic Detection of Histological Artifacts in Mouse Brain Slice Images.- Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features.- Representation Learning for Cross-Modality Classification.- Guideline-based Machine Learning for Standard Plane Extraction in 3D Cardiac Ultrasound.- A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images.- Bayesian Multiview Manifold Learning Applied to Hippocampus Shape and Clinical Score Data.- Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields.- Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI data.- Non-local Graph-based Regularization for Deformable Image Registration.- Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation. .
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Medical Computer Vision, MCV 2016, and of the International Workshop on Bayesian and grAphical Models for Biomedical Imaging, BAMBI 2016, held in Athens, Greece, in October 2016, held in conjunction with the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016. The 13 papers presented in MCV workshop and the 6 papers presented in BAMBI workshop were carefully reviewed and selected from numerous submissions. The goal of the MCV workshop is to explore the use of "big data" algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images. The BAMBI workshop aims to highlight the potential of using Bayesian or random field graphical models for advancing research in biomedical image analysis.
(source: Nielsen Book Data)

• Medical, health, biomedicine information.- Artificial intelligence for computer-aided diagnosis.- Data management, data mining, and knowledge discovery.- Development of new architectures and applications.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 7th International Conference on Health Information Science, HIS 2018, held in Cairns, QLD, Australia, in October 2018. The 13 full papers and 5 short papers presented were carefully reviewed and selected from 43 submissions. The papers feature multidisciplinary research results in health information science and systems that support health information management and health service delivery. They relate to all aspects of the conference scope, such as medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, and optimize the use of information in the health domain; data management, data mining, and knowledge discovery, management of public health, examination of standards, privacy and security issues; computer visualization and artificial intelligence for computer aided diagnosis; development of new architectures and applications for health information systems.
(source: Nielsen Book Data)

• Blood-flow estimation in the hepatic arteries based on 3D/2D angiography registration.- Automated quantification of blood flow velocity from time-resolved CT angiography.- Multiple device segmentation for fluoroscopic imaging using multi-task learning.- Segmentation of the Aorta Using Active Contours with Histogram-Based Descriptors.- Layer Separation in X-ray Angiograms for Vessel Enhancement with Fully Convolutional Network.- Generation of a HER2 breast cancer gold-standard using supervised learning from multiple experts.- Deep Learning-based Detection and Segmentation for BVS Struts in IVOCT Images.- Towards Automatic Measurement of Type B Aortic Dissection Parameters.- Prediction of FFR from IVUS Images using Machine Learning.- Deep Learning Retinal Vessel Segmentation From a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural Networks.- An Efficient and Comprehensive Labeling Tool for Large-scale Annotation of Fundus Images.- Crowd disagreement about medical images is informative.- Imperfect Segmentation Labels: How Much Do They Matter?.- Crowdsourcing annotation of surgical instruments in videos of cataract surgery.- Four-dimensional ASL MR angiography phantoms with noise learned by neural styling.- Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans.- Capsule Networks against Medical Imaging Data Challenges.- Fully Automatic Segmentation of Coronary Arteries based on Deep Neural Network in Intravascular Ultrasound Images.- Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos.- Radiology Objects in COntext (ROCO).- Improving out-of-sample prediction of quality of MRIQC.
• (source: Nielsen Book Data)

This book constitutes the refereed joint proceedings of the 7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the Third International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 9 full papers presented at CVII-STENT 2017 and the 12 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.
(source: Nielsen Book Data)

• Computer Aided Identification of Motion Disturbances Related to Parkinson's Disease
• Prediction of Severity and Treatment Outcome for ASD from fMRI
• Enhancement of Perivascular Spaces Using a Very Deep 3D Dense Network
• Generation of Amyloid PET Images via Conditional Adversarial Training for Predicting Progression to Alzheimer's Disease
• Prediction of Hearing Loss Based on Auditory Perception: A Preliminary Study
• Predictive Patient Care: Survival Model to Prevent Medication Non-adherence
• Joint Robust Imputation and Classification for Early Dementia Detection Using Incomplete Multi-Modality Data
• Shared Latent Structures Between Imaging Features and Biomarkers in Early Stages of Alzheimer's Disease
• Predicting Nucleus Basalis of Meynert Volume from Compartmental Brain Segmentations
• Multi-modal Neuroimaging Data Fusion via Latent Space Learning for Alzheimer's Disease Diagnosis
• Transfer Learning for Task Adaptation of Brain Lesion Assessment and Prediction of Brain Abnormalities Progression/Regression Using Irregularity Age Map in Brain MRI
• Multi-View Brain Network Prediction From a Source View Using Sample Selection via CCA-based Multi-Kernel Connectomic Manifold Learning
• Predicting Emotional Intelligence Scores From Multi-Session Functional Brain Connectomes
• Predictive Modeling of Longitudinal Data for Alzheimer's Disease Diagnosis Using RNNs
• Towards Continuous Health Diagnosis from Faces with Deep Learning
• XmoNet: A Fully Convolutional Network for Cross-Modality MR Image Inference
• 3D Convolutional Neural Network and Stacked Bidirectional Recurrent Neural Network for Alzheimer's Disease Diagnosis
• Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI
• Diffusion MRI Spatial Super-Resolution Using Generative Adversarialv Networks
• Prediction to Atrial Fibrillation Using Deep Convolutional Neural Networks.

This book constitutes the refereed proceedings of the First International Workshop on PRedictive Intelligence in MEdicine, PRIME 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 20 full papers presented were carefully reviewed and selected from 23 submissions. The main aim of the workshop is to propel the advent of predictive models in a broad sense, with application to medical data. Particularly, the workshop will admit papers describing new cutting-edge predictive models and methods that solve challenging problems in the medical field.

• Smart Hospital.- Online Health Community.- Mobile Health.- Medical Big Data and Healthcare Machine Learning.- Chronic Disease Management.- Health Informatics.
• (source: Nielsen Book Data)

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference for Smart Health, ICSH 2018, held in Wuhan, China, in July 2018.The 14 full papers and 21 short papers presented were carefully reviewed and selected from 49 submissions. They focus on studies on the principles, approaches, models, frameworks, new applications, and effects of using novel information technology to address healthcare problems and improve social welfare. The selected papers are organized into the following topics: smart hospital; online health community; mobile health; medical big data and healthcare machine learning; chronic disease management; and health informatics.
(source: Nielsen Book Data)

• Part I: Biomedical Engineering, Trends, Research and Technologies
• Vision Paper for Enabling Internet of Medical Robotics Things in Open Healthcare Platform 2030
• Stumbling Blocks of Utilizing Medical and Health Data: Success Factors Extracted from Australia-Japan Comparison
• Digital Financial Incentives for Improved Population Health in the Americas
• Part II: Advanced ICT for Medicine and Healthcare
• Trial Run of a Patient Call System using Mobile Devices
• Advance Watermarking Algorithm using SURF with DWT and DCT for CT Images
• Improving Depth Perception using Multiple Iso-Surfaces for Transparent Stereoscopic Visualization of Medical Volume Data
• Design and Simulation of a Robotic Manipulator for Laparoscopic Uterine Surgeries
• Self-Skill Training System for Chest Compressions in Neonatal Resuscitation Workshop
• Part III. Statistical Signal Processing and Artificial Intelligence
• Comparative Study of Pattern Recognition Methods for Predicting Glaucoma Diagnosis
• Research on Encrypted Face Recognition Algorithm Based on New Combined Chaotic Map and Neural Network
• A 3D Shrinking-and-Expanding Module with Channel Attention for Efficient Deep Learning-Based Super-Resolution
• Dynamic Facial Features in Positive-Emotional Speech for Identification of Depressive Tendencies
• Hand-Crafted and Deep Learning-Based Radiomics Models for Recurrence Prediction of Non-Small Cells Lung Cancers
• Weakly and Semi-supervised Deep Level Set Network for Automated Skin Lesion Segmentation
• Part IV. Support System for Medicine and Healthcare
• A Transcriptional Study of Oncogenes and Tumor Suppressors Altered by Copy Number Variations in Ovarian Cancer
• Analysis of Acoustic Features Affected by Residual Food in the Piriform Fossa Toward Early-Detection of Dysphagia
• Automatic Joint Space Distance Measurement Method for Rheumatoid Arthritis Medical Examinations
• Development of an Active Compression System for Venous Disease
• Design and Development of a Droplet-Based Microfluidics System Using Laser Fabrication Machining Techniques for a Lab on a Chip Device
• Design of a Novel MEMS-Based Microgripper with Hybrid Actuation to Determine Circulating Tumor Cell (CTC) Progression.

This book presents the proceedings of the KES International Conferences on Innovation in Medicine and Healthcare (KES-InMed-19), held in Split, Croatia, on June 17-19, 2020. Covering a number of key areas, including digital IT architecture in healthcare; advanced ICT for medicine and healthcare; biomedical engineering, trends, research and technologies; and healthcare support systems, this book is a valuable resource for researchers, managers, industrialists and anyone wishing to gain an overview of the latest research in these fields. .
(source: Nielsen Book Data)

• Sensor data synchronization in a IoT environment for infants motricity measurement.- A Real-time Algorithm for PPG Signal Processing During Intense Physical Activity.- Design and Testing of a Textile EMG Sensor for Prosthetic Control.- Design of a smart mechatronic system to combine garments for blind people: first insights IoT for Health applications and solutions.- Towards a smartwatch for cu-less blood pressure measurement using PPG signal and physiological features.- WiFi-enabled Automatic Eating Moment Monitoring Using Smartphones.- SocialBike: Quantified-self Data as Social Cue in Physical Activity.- Assisting Radiologists in X-Ray Diagnostics Design and Evaluation for Digital Forensic Ready Wireless Medical Systems.- An IoT-based Healthcare Ecosystem for Home Intelligent Assistant Services in Smart Homes.
• .
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 6th International Conference on Internet of Things (IoT) Technologies for HealthCare, HealthyIoT 2019, held in Braga, Portugal, in December 2019. The IoT as a set of existing and emerging technologies, notions and services can provide many solutions to delivery of electronic healthcare, patient care, and medical data management. The 10 revised full papers presented were carefully reviewed and selected from 26 submissions. The papers cover topics such as healthcare information systems, consumer health, health informatics, engineering, telecommunications, mathematics and statistics, life and medical sciences, and cloud computing.
(source: Nielsen Book Data)

• Improving quality and containing cost in health care and care for the elderly by using information technology.- Collecting the fruits of respect in entrepreneurship and management of organizations.- Friend or foe: Society in the area of tension between free data movement and data protection.- Bridging the digital divide: strengthening (health-) literacy and supporting trainings in information society. .
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 8th International Conference on Well-Being in the Information Society, WIS 2020, held in Turku, Finland, in August 2020. Due to the COVID-19 pandemic the conference was held online. The 19 revised full papers presented were carefully reviewed and selected from 25 submissions. The submitted papers present academic contributions on the topics of intersection of health, ICT and fruits of respect as seen from different directions and contexts. The paperd are organized in the following topical sections: improving quality and containing cost in health care and care for the elderly by using information technology; collecting the fruits of respect in entrepreneurship and management of organizations; friend or foe: society in the area of tension between free data movement and data protection; bridging the digital divide: strengthening (health-) literacy and supporting trainings in information society. .
(source: Nielsen Book Data)