Investigating Human Cancer with Computational Intelligence Techniques

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Publisher : Lulu.com
ISBN 13 : 0956151604
Total Pages : 138 pages
Book Rating : 4.9/5 (561 download)

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Book Synopsis Investigating Human Cancer with Computational Intelligence Techniques by : Alfredo Vellido

Download or read book Investigating Human Cancer with Computational Intelligence Techniques written by Alfredo Vellido and published by Lulu.com. This book was released on 2010-08 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human cancer is at an important frontier of medical research, and one where Computational Intelligence methods have made substantial inroads in recent years. Computational Intelligence research in cancer now reaches all biological scales from human population down to the phenotype and genotype. It is also fair to say that it reaches the complete range of cancer pathologies. This book does not aim to achieve such completeness of coverage. Instead, the studies included in it should provide readers with a broad palette and a hopefully useful taster of what Computational Intelligence methods can achieve in the field. This volume contains an overview of the field and a collection of eight leading-edge studies from research teams composed of experts in the field on various aspects of the subject.

Computational Intelligence in Cancer Diagnosis

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Publisher : Academic Press
ISBN 13 : 0323903533
Total Pages : 422 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Computational Intelligence in Cancer Diagnosis by : Janmenjoy Nayak

Download or read book Computational Intelligence in Cancer Diagnosis written by Janmenjoy Nayak and published by Academic Press. This book was released on 2023-04-12 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence in Cancer Diagnosis: Progress and Challenges provides insights into the current strength and weaknesses of different applications and research findings on computational intelligence in cancer research. The book improves the exchange of ideas and coherence among various computational intelligence methods and enhances the relevance and exploitation of application areas for both experienced and novice end-users. Topics discussed include neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolutionary computation, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. The book's chapters are written by international experts from both cancer research, oncology and computational sides to cover different aspects and make it comprehensible for readers with no background on informatics. Contains updated information about advanced computational intelligence, spanning the areas of neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolutionary computation, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems in diagnosing cancer diseases Discusses several cancer types, including their detection, treatment and prevention Presents case studies that illustrate the applications of intelligent computing in data analysis to help readers to analyze and advance their research in cancer

Artificial Intelligence Techniques In Breast Cancer Diagnosis And Prognosis

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Author :
Publisher : World Scientific
ISBN 13 : 9814492671
Total Pages : 350 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Artificial Intelligence Techniques In Breast Cancer Diagnosis And Prognosis by : Lakhmi C Jain

Download or read book Artificial Intelligence Techniques In Breast Cancer Diagnosis And Prognosis written by Lakhmi C Jain and published by World Scientific. This book was released on 2000-08-21 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main aim of this book is to present a sample of recent research on the application of novel artificial intelligence paradigms to the diagnosis and prognosis of breast cancer. These paradigms include neural networks, fuzzy logic and evolutionary computing. Artificial intelligence techniques offer advantages — such as adaptation, fault tolerance, learning and human-like behavior — over conventional computing techniques. The idea is to combine the pathological, intelligent and statistical approaches to enable simple and accurate diagnosis and prognosis.This book is the first of its kind on the topic of artificial intelligence in breast cancer. It presents the applications of artificial intelligence in breast cancer diagnosis and prognosis, and includes state-of-the-art concepts in the field. It contains contributions from Australia, Germany, Italy, UK and the USA.

Cancer Prediction for Industrial IoT 4.0

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Publisher : CRC Press
ISBN 13 : 1000508587
Total Pages : 219 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Cancer Prediction for Industrial IoT 4.0 by : Meenu Gupta

Download or read book Cancer Prediction for Industrial IoT 4.0 written by Meenu Gupta and published by CRC Press. This book was released on 2021-12-30 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines. Features • Covers the fundamentals, history, reality and challenges of cancer • Presents concepts and analysis of different cancers in humans • Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer • Offers real-world examples of cancer prediction • Reviews strategies and tools used in cancer prediction • Explores the future prospects in cancer prediction and treatment Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions. This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

Artificial Intelligence in Healthcare

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Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Recent Trends in Computational Intelligence Enabled Research

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Publisher : Academic Press
ISBN 13 : 0323851797
Total Pages : 420 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Recent Trends in Computational Intelligence Enabled Research by : Siddhartha Bhattacharyya

Download or read book Recent Trends in Computational Intelligence Enabled Research written by Siddhartha Bhattacharyya and published by Academic Press. This book was released on 2021-07-31 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques

Deep Learning for the Life Sciences

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Publisher : O'Reilly Media
ISBN 13 : 1492039802
Total Pages : 236 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for the Life Sciences by : Bharath Ramsundar

Download or read book Deep Learning for the Life Sciences written by Bharath Ramsundar and published by O'Reilly Media. This book was released on 2019-04-10 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare

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Publisher : Academic Press
ISBN 13 : 0128222611
Total Pages : 398 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Handbook of Computational Intelligence in Biomedical Engineering and Healthcare by : Janmenjoy Nayak

Download or read book Handbook of Computational Intelligence in Biomedical Engineering and Healthcare written by Janmenjoy Nayak and published by Academic Press. This book was released on 2021-04-08 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques. Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis. Presents a comprehensive handbook that covers an Introduction to Computational Intelligence in Biomedical Engineering and Healthcare, Computational Intelligence Techniques, and Advanced and Emerging Techniques in Computational Intelligence Helps readers analyze and do advanced research in specialty healthcare applications Includes links to websites, videos, articles and other online content to expand and support primary learning objectives

Computational Intelligence Methods for Bioinformatics and Biostatistics

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Publisher : Springer Nature
ISBN 13 : 3030345858
Total Pages : 334 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Computational Intelligence Methods for Bioinformatics and Biostatistics by : Maria Raposo

Download or read book Computational Intelligence Methods for Bioinformatics and Biostatistics written by Maria Raposo and published by Springer Nature. This book was released on 2020-01-22 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 15th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics., CIBB 2018, held in Caparica, Portugal, in September 2018. The 32 revised full papers were carefully reviewed and selected from 51 submissions. The papers present current trends at the edge of computer and life sciences, the application of computational intelligence to a system and synthetic biology and the consequent impact on innovative medicine were presented. Theoretical and experimental biologists also presented novel challenges and fostered multidisciplinary collaboration aiming to blend theory and practice, where the founding theories of the techniques used for modelling and analyzing biological systems are investigated and used for practical applications and the supporting technologies.

Human Cancer Diagnosis and Detection Using Exascale Computing

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Publisher : John Wiley & Sons
ISBN 13 : 1394197683
Total Pages : 340 pages
Book Rating : 4.3/5 (941 download)

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Book Synopsis Human Cancer Diagnosis and Detection Using Exascale Computing by : Kapil Joshi

Download or read book Human Cancer Diagnosis and Detection Using Exascale Computing written by Kapil Joshi and published by John Wiley & Sons. This book was released on 2024-02-21 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human Cancer Diagnosis and Detection Using Exascale Computing The book provides an in-depth exploration of how high-performance computing, particularly exascale computing, can be used to revolutionize cancer diagnosis and detection; it also serves as a bridge between the worlds of computational science and clinical oncology. Exascale computing has the potential to increase our ability in terms of computation to develop efficient methods for a better healthcare system. This technology promises to revolutionize cancer diagnosis and detection, ushering in an era of unprecedented precision, speed, and efficiency. The fusion of exascale computing with the field of oncology has the potential to redefine the boundaries of what is possible in the fight against cancer. The book is a comprehensive exploration of this transformative unification of science, medicine, and technology. It delves deeply into the realm of exascale computing and its profound implications for cancer research and patient care. The 18 chapters are authored by experts from diverse fields who have dedicated their careers to pushing the boundaries of what is achievable in the realm of cancer diagnosis and detection. The chapters cover a wide range of topics, from the fundamentals of exascale computing and its application to cancer genomics to the development of advanced imaging techniques and machine learning algorithms. Explored is the integration of data analytics, artificial intelligence, and high-performance computing to move cancer research to the next phase and support the creation of novel medical tools and technology for the detection and diagnosis of cancer. Audience This book has a wide audience from both computer sciences (information technology, computer vision, artificial intelligence, software engineering, applied mathematics) and the medical field (biomedical engineering, bioinformatics, oncology). Researchers, practitioners and students will find this groundbreaking book novel and very useful.

Machine Learning and Systems Biology in Genomics and Health

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Publisher : Springer Nature
ISBN 13 : 9811659931
Total Pages : 239 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Machine Learning and Systems Biology in Genomics and Health by : Shailza Singh

Download or read book Machine Learning and Systems Biology in Genomics and Health written by Shailza Singh and published by Springer Nature. This book was released on 2022-02-04 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.

Decision Making in Aviation

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Publisher : Routledge
ISBN 13 : 135157003X
Total Pages : 655 pages
Book Rating : 4.3/5 (515 download)

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Book Synopsis Decision Making in Aviation by : Don Harris

Download or read book Decision Making in Aviation written by Don Harris and published by Routledge. This book was released on 2017-07-05 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision making pervades every aspect of life: people make hundreds of decisions every day. The vast majority of these are trivial and without a right or wrong answer. In some respects there is also nothing extraordinary about pilot decision making. It is only the setting that is different - the underlying cognitive processes are just the same. However, it is the context and the consequences of a poor decision which serve to differentiate aeronautical decision making. Decisions on the flight deck are often made with incomplete information and while under time pressure. The implications for inadequate performance is much more serious than in many other professions. Poor decisions are implicated in over half of all aviation accidents. This volume contains key papers published over the last 25 years providing an overview of the major paradigms by which aeronautical decision making has been investigated. Furthermore, decision making does not occur in isolation. It is a joint function of the flight tasks; knowledge; equipment on the flight deck and other stressors. In this volume of collected papers, works from leading authors in the field consider all these aspects of aeronautical decision making.

Artificial Intelligence in Medical Imaging

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Publisher : Springer
ISBN 13 : 3319948784
Total Pages : 373 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Artificial Intelligence in Medical Imaging by : Erik R. Ranschaert

Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0

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Publisher : Springer Nature
ISBN 13 : 3031563220
Total Pages : 317 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 by : D. Jude Hemanth

Download or read book Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 written by D. Jude Hemanth and published by Springer Nature. This book was released on with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence for Translational Pharmacology

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Publisher : Frontiers Media SA
ISBN 13 : 288963888X
Total Pages : 129 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Artificial Intelligence for Translational Pharmacology by : Zhi-Liang Ji

Download or read book Artificial Intelligence for Translational Pharmacology written by Zhi-Liang Ji and published by Frontiers Media SA. This book was released on 2020-07-28 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Intelligence in Oncology

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Publisher : Springer Nature
ISBN 13 : 9811692211
Total Pages : 474 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Computational Intelligence in Oncology by : Khalid Raza

Download or read book Computational Intelligence in Oncology written by Khalid Raza and published by Springer Nature. This book was released on 2022-03-01 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book encapsulates recent applications of CI methods in the field of computational oncology, especially cancer diagnosis, prognosis, and its optimized therapeutics. The cancer has been known as a heterogeneous disease categorized in several different subtypes. According to WHO’s recent report, cancer is a leading cause of death worldwide, accounting for over 10 million deaths in the year 2020. Therefore, its early diagnosis, prognosis, and classification to a subtype have become necessary as it facilitates the subsequent clinical management and therapeutics plan. Computational intelligence (CI) methods, including artificial neural networks (ANNs), fuzzy logic, evolutionary computations, various machine learning and deep learning, and nature-inspired algorithms, have been widely utilized in various aspects of oncology research, viz. diagnosis, prognosis, therapeutics, and optimized clinical management. Appreciable progress has been made toward the understanding the hallmarks of cancer development, progression, and its effective therapeutics. However, notwithstanding the extrinsic and intrinsic factors which lead to drastic increment in incidence cases, the detection, diagnosis, prognosis, and therapeutics remain an apex challenge for the medical fraternity. With the advent in CI-based approaches, including nature-inspired techniques, and availability of clinical data from various high-throughput experiments, medical consultants, researchers, and oncologists have seen a hope to devise and employ CI in various aspects of oncology. The main aim of the book is to occupy state-of-the-art applications of CI methods which have been derived from core computer sciences to back medical oncology. This edited book covers artificial neural networks, fuzzy logic and fuzzy inference systems, evolutionary algorithms, various nature-inspired algorithms, and hybrid intelligent systems which are widely appreciated for the diagnosis, prognosis, and optimization of therapeutics of various cancers. Besides, this book also covers multi-omics exploration, gene expression analysis, gene signature identification of cancers, genomic characterization of tumors, anti-cancer drug design and discovery, drug response prediction by means of CI, and applications of IoT, IoMT, and blockchain technology in cancer research.

Data Analytics in Bioinformatics

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Publisher : John Wiley & Sons
ISBN 13 : 1119785618
Total Pages : 544 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Data Analytics in Bioinformatics by : Rabinarayan Satpathy

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.