Artificial Computation In Biology And Medicine

DOWNLOAD

Download Artificial Computation In Biology And Medicine PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Artificial Computation In Biology And Medicine book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Artificial Intelligence In Medicine

DOWNLOAD
Author : David Riaño
language : en
Publisher: Springer
Release Date : 2019-06-19

Artificial Intelligence In Medicine written by David Riaño and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-19 with Computers categories.

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Artificial Neural Networks In Medicine And Biology

DOWNLOAD
Author : H. Malmgren
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Artificial Neural Networks In Medicine And Biology written by H. Malmgren and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.

This book contains the proceedings of the conference ANNIMAB-l, held 13-16 May 2000 in Goteborg, Sweden. The conference was organized by the Society for Artificial Neural Networks in Medicine and Biology (ANNIMAB-S), which was established to promote research within a new and genuinely cross-disciplinary field. Forty-two contributions were accepted for presentation; in addition to these, S invited papers are also included. Research within medicine and biology has often been characterised by application of statistical methods for evaluating domain specific data. The growing interest in Artificial Neural Networks has not only introduced new methods for data analysis, but also opened up for development of new models of biological and ecological systems. The ANNIMAB-l conference is focusing on some of the many uses of artificial neural networks with relevance for medicine and biology, specifically: • Medical applications of artificial neural networks: for better diagnoses and outcome predictions from clinical and laboratory data, in the processing of ECG and EEG signals, in medical image analysis, etc. More than half of the contributions address such clinically oriented issues. • Uses of ANNs in biology outside clinical medicine: for example, in models of ecology and evolution, for data analysis in molecular biology, and (of course) in models of animal and human nervous systems and their capabilities. • Theoretical aspects: recent developments in learning algorithms, ANNs in relation to expert systems and to traditional statistical procedures, hybrid systems and integrative approaches.

Advances In Artificial Intelligence Computation And Data Science

DOWNLOAD
Author : Tuan D. Pham
language : en
Publisher:
Release Date : 2021

Advances In Artificial Intelligence Computation And Data Science written by Tuan D. Pham and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.

Artificial intelligence (AI) has become pervasive in most areas of research and applications. While computation can significantly reduce mental efforts for complex problem solving, effective computer algorithms allow continuous improvement of AI tools to handle complexity-in both time and memory requirements-for machine learning in large datasets. Meanwhile, data science is an evolving scientific discipline that strives to overcome the hindrance of traditional skills that are too limited to enable scientific discovery when leveraging research outcomes. Solutions to many problems in medicine and life science, which cannot be answered by these conventional approaches, are urgently needed for society. This edited book attempts to report recent advances in the complementary domains of AI, computation, and data science with applications in medicine and life science. The benefits to the reader are manifold as researchers from similar or different fields can be aware of advanced developments and novel applications that can be useful for either immediate implementations or future scientific pursuit. Features: Considers recent advances in AI, computation, and data science for solving complex problems in medicine, physiology, biology, chemistry, and biochemistry Provides recent developments in three evolving key areas and their complementary combinations: AI, computation, and data science Reports on applications in medicine and physiology, including cancer, neuroscience, and digital pathology Examines applications in life science, including systems biology, biochemistry, and even food technology This unique book, representing research from a team of international contributors, has not only real utility in academia for those in the medical and life sciences communities, but also a much wider readership from industry, science, and other areas of technology and education. Tuan D. Pham is professor and founding director of the Center for Artificial Intelligence at Prince Mohammad Bin Fahd University, Saudi Arabia. Hong Yan is currently chair professor of computer engineering at City University of Hong Kong. Dr. Muhammad Waqar Ashraf is professor and dean of College of Sciences & Human Studies at Prince Mohammad Bin Fahd University. Folke Sjöberg is professor of burn surgery and critical care at Linköping University, Sweden, and director of the Burn Center at the Linköping University Hospital.

Medical Applications Of Artificial Intelligence

DOWNLOAD
Author : Arvin Agah
language : en
Publisher: CRC Press
Release Date : 2013-11-06

Medical Applications Of Artificial Intelligence written by Arvin Agah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-06 with Medical categories.

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must dev

Automated Reasoning For Systems Biology And Medicine

DOWNLOAD
Author : Pietro Liò
language : en
Publisher: Springer
Release Date : 2019-06-11

Automated Reasoning For Systems Biology And Medicine written by Pietro Liò and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-11 with Science categories.

This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the development of algorithms that yield trustworthy answers, providing a basis of sound logical reasoning. For example, in the semiconductor industry formal verification is instrumental to ensuring that chip designs are free of defects (or “bugs”). Over the past 15 years, systems biology and systems medicine have been introduced in an attempt to understand the enormous complexity of life from a computational point of view. This has generated a wealth of new knowledge in the form of computational models, whose staggering complexity makes manual analysis methods infeasible. Sound, trusted, and automated means of analysing the models are thus required in order to be able to trust their conclusions. Above all, this is crucial to engineering safe biomedical devices and to reducing our reliance on wet-lab experiments and clinical trials, which will in turn produce lower economic and societal costs. Some examples of the questions addressed here include: Can we automatically adjust medications for patients with multiple chronic conditions? Can we verify that an artificial pancreas system delivers insulin in a way that ensures Type 1 diabetic patients never suffer from hyperglycaemia or hypoglycaemia? And lastly, can we predict what kind of mutations a cancer cell is likely to undergo? This book brings together leading researchers from a number of highly interdisciplinary areas, including: · Parameter inference from time series · Model selection · Network structure identification · Machine learning · Systems medicine · Hypothesis generation from experimental data · Systems biology, systems medicine, and digital pathology · Verification of biomedical devices “This book presents a comprehensive spectrum of model-focused analysis techniques for biological systems ...an essential resource for tracking the developments of a fast moving field that promises to revolutionize biology and medicine by the automated analysis of models and data.”Prof Luca Cardelli FRS, University of Oxford

Artificial Intelligence And Molecular Biology

DOWNLOAD
Author : Lawrence Hunter
language : en
Publisher:
Release Date : 1993

Artificial Intelligence And Molecular Biology written by Lawrence Hunter and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computers categories.

These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. The enormous amount of data generated by the Human Genome Project and other large-scale biological research has created a rich and challenging domain for research in artificial intelligence. These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book. Lawrence Hunter is Director of the Machine Learning Project at the National Library of Medicine, National Institutes of Health.

Computational Intelligence For Oncology And Neurological Disorders

DOWNLOAD
Author : Mrutyunjaya Panda
language : en
Publisher: CRC Press
Release Date : 2024-07-15

Computational Intelligence For Oncology And Neurological Disorders written by Mrutyunjaya Panda and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-15 with Computers categories.

With the advent of computational intelligence-based approaches, such as bio-inspired techniques, and the availability of clinical data from various complex experiments, medical consultants, researchers, neurologists, and oncologists, there is huge scope for CI-based applications in medical oncology and neurological disorders. This book focuses on interdisciplinary research in this field, bringing together medical practitioners dealing with neurological disorders and medical oncology along with CI investigators. The book collects high-quality original contributions, containing the latest developments or applications of practical use and value, presenting interdisciplinary research and review articles in the field of intelligent systems for computational oncology and neurological disorders. Drawing from work across computer science, physics, mathematics, medical science, psychology, cognitive science, oncology, and neurobiology among others, it combines theoretical, applied, computational, experimental, and clinical research. It will be of great interest to any neurology or oncology researchers focused on computational approaches.

Analyzing Network Data In Biology And Medicine

DOWNLOAD
Author : Nataša Pržulj
language : en
Publisher: Cambridge University Press
Release Date : 2019-03-28

Analyzing Network Data In Biology And Medicine written by Nataša Pržulj and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-28 with Language Arts & Disciplines categories.

Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.

Bio Inspired Artificial Intelligence

DOWNLOAD
Author : Dario Floreano
language : en
Publisher: MIT Press
Release Date : 2023-04-04

Bio Inspired Artificial Intelligence written by Dario Floreano and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-04 with Computers categories.

A comprehensive introduction to new approaches in artificial intelligence and robotics that are inspired by self-organizing biological processes and structures. New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization. Examples of these new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, biorobotics, and swarm intelligence—to mention only a few. This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers. Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems—including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems. Chapters end with a concluding overview and suggested reading.

Computational Biology And Machine Learning For Metabolic Engineering And Synthetic Biology

DOWNLOAD
Author : Kumar Selvarajoo
language : en
Publisher: Springer Nature
Release Date : 2022-10-13

Computational Biology And Machine Learning For Metabolic Engineering And Synthetic Biology written by Kumar Selvarajoo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-13 with Science categories.

This volume provides protocols for computational, statistical, and machine learning methods that are mainly applied to the study of metabolic engineering, synthetic biology, and disease applications. These techniques support the latest progress in cross-disciplinary research that integrates the different scales of biological complexity. The topics covered in this book are geared toward researchers with a background in engineering, computational analytical, and modeling experience and cover a broad range of topics in computational and machine learning approaches. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and practical, Computational Biology and Machine Learning for Metabolic Engineering and Synthetic Biology is a valuable resource for any researcher or scientist who wants to learn more about the latest computational methods and how they are applied toward the understanding and prediction of complex biology.