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Artificial Intelligence for Computational Modeling of the Heart

Artificial Intelligence for Computational Modeling of the Heart
  • Author : Tommaso Mansi
  • Publsiher : Academic Press
  • Release : 01 December 2019
  • ISBN : 012817594X
  • Pages : 260 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKArtificial Intelligence for Computational Modeling of the Heart

Summary:
Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation


Artificial Intelligence for Computational Modeling of the Heart

Artificial Intelligence for Computational Modeling of the Heart
  • Author : Tommaso Mansi,Tiziano Passerini,Dorin Comaniciu
  • Publisher : Academic Press
  • Release : 01 December 2019
GET THIS BOOKArtificial Intelligence for Computational Modeling of the Heart

Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model


Computational Cardiovascular Mechanics

Computational Cardiovascular Mechanics
  • Author : Julius M. Guccione,Ghassan Kassab,Mark B. Ratcliffe
  • Publisher : Springer Science & Business Media
  • Release : 08 January 2010
GET THIS BOOKComputational Cardiovascular Mechanics

Computational Cardiovascular Mechanics provides a cohesive guide to creating mathematical models for the mechanics of diseased hearts to simulate the effects of current treatments for heart failure. Clearly organized in a two part structure, this volume discusses various areas of computational modeling of cardiovascular mechanics (finite element modeling of ventricular mechanics, fluid dynamics) in addition to a description an analysis of the current applications used (solid FE modeling, CFD). Edited by experts in the field, researchers involved with biomedical and


Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges

Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges
  • Author : Esther Puyol Anton,Mihaela Pop,Maxime Sermesant,Victor Campello,Alain Lalande,Karim Lekadir,Avan Suinesiaputra,Oscar Camara,Alistair Young
  • Publisher : Springer Nature
  • Release : 28 January 2021
GET THIS BOOKStatistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges

This book constitutes the proceedings of the 11th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2020, as well as two challenges: M&Ms - The Multi-Centre, Multi-Vendor, Multi-Disease Segmentation Challenge, and EMIDEC - Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI Challenge. The 43 full papers included in this volume were carefully reviewed and selected from 70 submissions. They deal with cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction,



Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges
  • Author : Mihaela Pop,Maxime Sermesant,Jichao Zhao,Shuo Li,Kristin McLeod,Alistair Young,Kawal Rhode,Tommaso Mansi
  • Publisher : Springer
  • Release : 05 March 2019
GET THIS BOOKStatistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges

This book constitutes the thoroughly refereed post-workshop proceedings of the 9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 52 revised full workshop papers were carefully reviewed and selected from 60 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different


Computational Models of the Heart for Planning and Treatment of Outflow Tract Ventricular Arrhythmias

Computational Models of the Heart for Planning and Treatment of Outflow Tract Ventricular Arrhythmias
  • Author : Rubén Doste Beltrán
  • Publisher : Anonim
  • Release : 05 March 2021
GET THIS BOOKComputational Models of the Heart for Planning and Treatment of Outflow Tract Ventricular Arrhythmias

The purpose of this thesis was to develop personalised cardiovascular therapy guided by multimodal noninvasive imaging and simulations, combined with artificial intelligence tools, for the management of the outflow tract ventricular arrhythmias. The main contributions of this thesis are twofold: -We propose a pipeline to build heart computational models for simulation of ventricular tachycardia that incorporates a new specific rule-base method for fiber generation, including the ventricular outflow tracts. The pipeline allows carrying out multiscale simulations, obtaining the patient ECG




Patient-Specific Computational Modeling

Patient-Specific Computational Modeling
  • Author : Begoña Calvo Lopez,Estefanía Peña
  • Publisher : Springer Science & Business Media
  • Release : 20 May 2012
GET THIS BOOKPatient-Specific Computational Modeling

This book addresses patient-specific modeling. It integrates computational modeling, experimental procedures, imagine clinical segmentation and mesh generation with the finite element method (FEM) to solve problems in computational biomedicine and bioengineering. Specific areas of interest include cardiovascular problems, ocular and muscular systems and soft tissue modeling. Patient-specific modeling has been the subject of serious research over the last seven years and interest in the area is continually growing and this area is expected to further develop in the near future.



Artificial Intelligence in Precision Health

Artificial Intelligence in Precision Health
  • Author : Debmalya Barh
  • Publisher : Academic Press
  • Release : 04 March 2020
GET THIS BOOKArtificial Intelligence in Precision Health

Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug


Machine Learning and Systems Engineering

Machine Learning and Systems Engineering
  • Author : Sio-Iong Ao,Burghard B. Rieger,Mahyar Amouzegar
  • Publisher : Springer Science & Business Media
  • Release : 05 October 2010
GET THIS BOOKMachine Learning and Systems Engineering

A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October 20-22, 2009, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2009). Machine Learning and Systems Engineering contains forty-six revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Expert system, Intelligent decision making, Knowledge-based systems, Knowledge extraction, Data analysis tools, Computational biology, Optimization algorithms, Experiment designs, Complex system identification, Computational modeling,


Statistical Atlases and Computational Models of the Heart

Statistical Atlases and Computational Models of the Heart
  • Author : Oscar Camara,Mihaela Pop,Kawal Rhode,Maxime Sermesant,Nic Smith,Alistair Young
  • Publisher : Springer Science & Business Media
  • Release : 03 September 2010
GET THIS BOOKStatistical Atlases and Computational Models of the Heart

computationalmodelswith experimentaldata. A completedatasetwasprovided in advance, containing the cardiac geometry and ?bre orientations from MRI as well as epicardial transmembrane potentials from optical mapping.


Proceedings

Proceedings
  • Author : American Association for Artificial Intelligence
  • Publisher : Aaai Press
  • Release : 05 March 1998
GET THIS BOOKProceedings

AAAI proceedings describe innovative concepts, techniques, perspectives, and observations that present promising research directions in artificial intelligence.