In Silico Clinical Trials for Cardiovascular Disease A Finite Element and Machine Learning Approach /

This book covers in silico clinical trials of cardiovascular disease using a finite element and machine learning approach. Part I describes the fundamentals as well as the latest developments in the field: finite element modeling, system biology modeling for drug optimization, artificial intelligenc...

Whakaahuatanga katoa

I tiakina i:
Ngā taipitopito rārangi puna kōrero
Kaituhi rangatōpū: SpringerLink (Online service)
Ētahi atu kaituhi: Filipović, Nenad (Editor)
Hōputu: Tāhiko īPukapuka
Reo:Ingarihi
I whakaputaina: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Putanga:1st ed. 2024.
Ngā marau:
Urunga tuihono:https://doi.org/10.1007/978-3-031-60044-9
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505 0 |a Chapter 1 - Heart physiology and heart diseases, Djordje Jakovljevic, Nenad Filipovic -- Chapter 2 - Finite element modeling, Nenad Filipovic -- Chapter 3 - System biology modeling for drug optimization, Marko Zivanovic, Nenad Filipovic -- Chapter 4 - Artificial intelligence approach for medical image processing, Tijana Sustersic, Nenad Filipovic.-Chapter 5 - Pharmacokinetic and AI modeling, Lazar Velicki, Nenad Filipovic -- Chapter 6 - Molecular micro modeling of heart muscle, Momcilo Prodanovic, Nenad Filipovic -- Chapter 7 - Use case: Risk stratification of cardiomyopathy disease, Lazar Dasic, Nenad Filipovic -- Chapter 8 - Use case: Surrogate AI model for left ventricle modeling, Bogdan Milicevic, Nenad Filipovic -- Chapter 9 - Use case: Carotid artery plaque modeling, Andjela Blagojevic, Nenad Filipovic -- Chapter 10 - Use case: Stent deployment for coronary artery, Miljan Milosevic, Nenad Filipovic -- Chapter 11 - Use case: Balloon deployment for peripheral arteries. Aleksandra Vulovic, Nenad Filipovic -- Chapter 12 - Use case: Aorta stenosis modeling, Smiljana Tomasevic, Nenad Filipovic -- Chapter 13 - Use case: Stent biodegradation modeling, Dalibor Nikolic, Nenad Filipovic. 
520 |a This book covers in silico clinical trials of cardiovascular disease using a finite element and machine learning approach. Part I describes the fundamentals as well as the latest developments in the field: finite element modeling, system biology modeling for drug optimization, artificial intelligence approach for medical image processing, as well as pharmacokinetic and AI modeling. Part II provides use cases to describe how in silico clinical trials of cardiovascular disease are applied to specific cardiovascular diseases: carotid artery plaque modeling, aorta stenosis modeling, stent biodegradation modeling, surrogate AI model for left ventricle modeling, and more. This book is geared toward upper-level undergraduate and graduate students as well as for researchers in the domains of bioengineering, biomechanics, biomedical engineering and medicine. 
532 8 |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. 
532 8 |a No reading system accessibility options actively disabled 
532 8 |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com 
650 0 |a Cardiovascular system. 
650 0 |a Physiology. 
650 0 |a Machine learning. 
650 0 |a Artificial intelligence. 
650 0 |a Drug delivery systems. 
650 1 4 |a Cardiovascular Physiology. 
650 2 4 |a Machine Learning. 
650 2 4 |a Artificial Intelligence. 
650 2 4 |a Drug Delivery. 
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