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This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks. Combining theory and practice, this book is suitable for the graduate or advanced undergraduate level classroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter notebooks, which can be downloaded from the book website.

This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19–21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications.

This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19–21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications.

Advances in experimental technologies have given rise to tremendous amounts of biology data. This not only offers valuable sources of data to help understand biological evolution and functional mechanisms, but also poses challenges for accurate and effective data analysis. This book offers an essential introduction to the theoretical and practical aspects of association analysis, including data pre-processing, data mining methods/algorithms, and tools that are widely applied for computational biology. It covers significant recent advances in the field, both foundational and application-oriented, helping readers understand the basic principles and emerging techniques used to discover interesting association patterns in diverse and heterogeneous biology data, such as structure-function correlations, and complex networks with gene/protein regulation. The main results and approaches are described in an easy-to-follow way and accompanied by sufficientreferences and suggestions for future research. This carefully edited monograph is intended to provide investigators in the fields of data mining, machine learning, artificial intelligence, and bioinformatics with a profound guide to the role of association analysis in computational biology. It is also very useful as a general source of information on association analysis, and as an overall accompanying course book and self-study material for graduate students and researchers in both computer science and bioinformatics.

This book provides an updated and in-depth introduction to the application of multiobjective optimization techniques in bioinformatics. In particular, it presents multiobjective solutions to a range of complex real-world bioinformatics problems. The authors first provide a comprehensive yet concise and self-contained introduction to relevant preliminary methodical constructions such as genetic algorithms, multiobjective optimization, data mining and several challenges in the bioinformatics domain. This is followed by several systematic applications of these techniques to real-world bioinformatics problems in the areas of gene expression and network biology. The book also features detailed theoretical and mathematical notes to facilitate reader comprehension. The book offers a valuable asset for a broad range of readers – from undergraduate to postgraduate, and as a textbook or reference work. Researchers and professionals can use the book not only to enrich their knowledge of multiobjective optimization and bioinformatics, but also as a comprehensive reference guide to applying and devising novel methods in bioinformatics and related domains.

Dieses Buch umfasst und beschäftigt sich mit den jüngsten Fortschritten und modernsten Anwendungen von naturinspirierten Computertechniken (NIC) im Bereich der Bioinformatik und der Computerbiologie, die die medizinischen Wissenschaften bei verschiedenen klinischen Anwendungen unterstützen können. Dieser Sammelband befasst sich mit den grundlegenden Anwendungen, dem Umfang und den Zukunftsperspektiven von NIC-Techniken in der Bioinformatik, einschließlich der Erstellung von Genomprofilen, der Klassifizierung von Genexpressionsdaten, der DNA-Berechnung, der System- und Netzwerkbiologie, der Lösung von Komplikationen bei personalisierten Therapien, der antimikrobiellen Resistenz bei bakteriellen Krankheitserregern und der computergestützten Entwicklung von Arzneimitteln, deren Entdeckung und Therapie. Darüber hinaus wird die Rolle von NIC-Techniken bei verschiedenen Krankheiten und Störungen behandelt, einschließlich Krebserkennung und -diagnose, Brustkrebs, Erkennung von Lungenkrankheiten, Krankheits-Biomarkern und Identifizierung potenzieller Therapeutika.

This book gathers high-quality research papers presented at the 4th International Conference on Frontiers in Computing and Systems (COMSYS 2023) held at Indian Institute of Technology Mandi, Himachal Pradesh, India, during 16–17 October 2023. The book is divided into two volumes, and it covers research in “cyber-physical systems for real-life applications” pertaining to AI, machine learning and data science; devices, circuits, and systems; computational biology, biomedical informatics, and network medicine; communication networks, cloud computing, and IoT; image, video, and signal processing; and security and privacy.

This book gathers high-quality research papers presented at the 4th International Conference on Frontiers in Computing and Systems (COMSYS 2023) held at Indian Institute of Technology Mandi, Himachal Pradesh, India, during 16–17 October 2023. The book is divided into two volumes, and it covers research in “cyber-physical systems for real-life applications” pertaining to AI, machine learning and data science; devices, circuits, and systems; computational biology, biomedical informatics, and network medicine; communication networks, cloud computing, and IoT; image, video, and signal processing; and security and privacy.

This two-volume set LNBI 14881-14882 constitutes - in conjunction with the 13-volume set LNCS 14862-14874 and the 6-volume set LNAI 14875-14880 - the refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024. The total of 863 regular papers were carefully reviewed and selected from 2189 submissions. The intelligent computing annual conference primarily aims to promote research, development and application of advanced intelligent computing techniques by providing a vibrant and effective forum across a variety of disciplines. This conference has a further aim of increasing the awareness of industry of advanced intelligent computing techniques and the economic benefits that can be gained by implementing them. The intelligent computing technology includes a range of techniques such as Artificial Intelligence, Pattern Recognition, Evolutionary Computing, Informatics Theories and Applications, Computational Neuroscience & Bioscience, Soft Computing, Human Computer Interface Issues, etc.

This two-volume set LNBI 14881-14882 constitutes - in conjunction with the 13-volume set LNCS 14862-14874 and the 6-volume set LNAI 14875-14880 - the refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024. The total of 863 regular papers were carefully reviewed and selected from 2189 submissions. The intelligent computing annual conference primarily aims to promote research, development and application of advanced intelligent computing techniques by providing a vibrant and effective forum across a variety of disciplines. This conference has a further aim of increasing the awareness of industry of advanced intelligent computing techniques and the economic benefits that can be gained by implementing them. The intelligent computing technology includes a range of techniques such as Artificial Intelligence, Pattern Recognition, Evolutionary Computing, Informatics Theories and Applications, Computational Neuroscience & Bioscience, Soft Computing, Human Computer Interface Issues, etc.

This book constitutes the refereed proceedings of the 20th International Symposium on Bioinformatics Research and Applications, ISBRA 2024, held in Kunming, China, in July 19–21, 2024. The 93 full papers included in this book were carefully reviewed and selected from 236 submissions. The symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications.

This book is for individuals with a scientific background who aspire to apply machine learning within various natural science disciplines—such as physics, chemistry, biology, medicine, psychology and many more. It elucidates core mathematical concepts in an accessible and straightforward manner, maintaining rigorous mathematical integrity. For readers more versed in mathematics, the book includes advanced sections that are not prerequisites for the initial reading. It ensures concepts are clearly defined and theorems are proven where it's pertinent. Machine learning transcends the mere implementation and training of algorithms; it encompasses the broader challenges of constructing robust datasets, model validation, addressing imbalanced datasets, and fine-tuning hyperparameters. These topics are thoroughly examined within the text, along with the theoretical foundations underlying these methods. Rather than concentrating on particular algorithms this book focuses on the comprehensive concepts and theories essential for their application. It stands as an indispensable resource for any scientist keen on integrating machine learning effectively into their research. Numerous texts delve into the technical execution of machine learning algorithms, often overlooking the foundational concepts vital for fully grasping these methods. This leads to a gap in using these algorithms effectively across diverse disciplines. For instance, a firm grasp of calculus is imperative to comprehend the training processes of algorithms and neural networks, while linear algebra is essential for the application and efficient training of various algorithms, including neural networks. Absent a solid mathematical base, machine learning applications may be, at best, cursory, or at worst, fundamentally flawed. This book lays the foundation for a comprehensive understanding of machine learning algorithms and approaches.

This book constitutes the Third 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, on September 22, 2022.The 22 contributions presented, as well as an overview paper, were carefully reviewed and selected from 24 submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 883 delineated PET/CT images was made available for training.

The book presents a conceptual and methodological basis for the mathematical and computational analysis of genomes. Genomes are containers of biological information, which direct the cell functions and the evolution of organisms. Combinatorial, probabilistic, and informational aspects are fundamental ingredients of any mathematical investigation of genomes aimed at providing mathematical principles for extracting the information that they contain. The topics presented in the book include research themes developed by authors in the last 15 years, and in many aspects, the book continues a preceding volume (Vincenzo Manca, Infobiotics: Information in biotic systems, Springer, 2013). The main inspiring idea of the book is an informational perspective to Genomics. Information is the most recent, among the fundamental mathematical and physical concepts developed in the last two centuries. It has revolutionized the whole science and continues, in this direction, to dominate the trends of the contemporary science. In fact, any discipline collects data from observations, by providing theories able to explain, predict, and dominate natural phenomena. But data are containers of information, whence information is essential in any scientific elaboration. Many open problems in deciphering genomes will be addressed, by showing an informational approach to the discovery of “genome languages”, according to which genomic texts are written. Life strategies, at many levels of organization, are encoded in these texts, and randomness has a crucial role in the birth and in the development of biological information, where the interplay of casualty and computation is probably the most secret key of life intelligence.

Machine learning and artificial intelligence have propelled research across various molecular science disciplines thanks to the rapid progress in computing hardware, algorithms, and data accumulation. This book presents recent machine learning applications in the broad research field of molecular sciences. Written by an international group of renowned experts, this edited volume covers both the machine learning methodologies and state-of-the-art machine learning applications in a wide range of topics in molecular sciences, from electronic structure theory to nuclear dynamics of small molecules, to the design and synthesis of large organic and biological molecules. This book is a valuable resource for researchers and students interested in applying machine learning in the research of molecular sciences.

This two-volume set LNCS 14134 and LNCS 14135 constitutes the refereed proceedings of the 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, held in Ponta Delgada, Portugal, during June 19–21, 2023.The 108 full papers presented in this two-volume set were carefully reviewed and selected from 149 submissions.The papers in Part I are organized in topical sections on advanced topics in computational intelligence; advances in artificial neural networks; ANN HW-accelerators; applications of machine learning in biomedicine and healthcare; and applications of machine learning in time series analysis. The papers in Part II are organized in topical sections on deep learning and applications; deep learning applied to computer vision and robotics; general applications of artificial intelligence; interaction with neural systems in both health and disease; machine learning for 4.0 industry solutions; neural networks in chemistry and materialcharacterization; ordinal classification; real world applications of BCI systems; and spiking neural networks: applications and algorithms.

This book includes selected papers from the 6th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2022), held in Coimbatore, India, from November 18 to 19, 2022. This volume presents state-of-the-art research innovations in computational vision and bio-inspired techniques. It includes theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems.

This book constitutes the refereed proceedings of the 19th International Symposium on Bioinformatics Research and Applications, ISBRA 2023, held in Wrocław, Poland, during October 9–12, 2023.The 28 full papers and 16 short papers included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: reconciling inconsistent molecular structures from biochemical databases; radiology report generation via visual recalibration and context gating-aware; sequence-based nanobody-antigen binding prediction; and hist2Vec: kernel-based embeddings for biological sequence classification.

This book constitutes the refereed proceedings of the 21st International Conference on Computational Methods in Systems Biology, CMSB 2023, held in Luxembourg City, Luxembourg, during September 13–15, 2023. The 14 full papers and 3 tool papers presented in this book were carefully reviewed and selected from 28 submissions. CMSB focuses on modeling, simulation, analysis, design and control of biological systems and covers the broad field of computational methods and tools in systems and synthetic biology and their applications.

This book constitutes the proceedings of the 16th Brazilian Symposium on Bioinformatics on Advances in Bioinformatics and Computational Biology, BSB 2023, which took place in Curitiba, Brazil, in June 2023. The 11 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 24 submissions. The papers focus on bioinformatics, computational biology, Biological Databases, Biological Networks, Cheminformatics, Evolutionary Genomics, Computational Proteomics, Systems Biology, Drug Design, Genomics, Machine Learning applications in Bioinformatics, Metagenomics, Molecular Docking and Modeling, Molecular Evolution and Phylogenetics, Protein Structure and Modeling, Proteomics, Transcriptomics, Single-Cell Analysis, Workflows in Bioinformatics.

Unique selling point: Advanced AI solutions for problems in genetics, virology, and related areas of life science Core audience: Researchers in bioinformatics Place in the market: High-level reference book on advanced applied technology

This book is a revised version of the PhD dissertation written by the author to receive her PhD from the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy. The work deals with one of the central objectives of the European Research Council project “Data-Driven Genomic Computing”, i.e., building an integrated repository for genomic data. It reflects the research adventure that starts from modeling biological data, goes through the challenges of integrating complex data and their describing metadata and finally builds tools for searching the data empowered by a semantic layer. The results of this thesis are part of a broad vision: the availability of conceptual models, related databases, and search systems for both humans and viruses genomics will provide important opportunities for research, especially if virus data will be connected to its host, the human being, who is the provider of genomic and phenotype information. In 2023, the PhD dissertation won the CAiSE PhD Award, granted to outstanding PhD theses in the field of information systems engineering.

This book broadly covers the given spectrum of disciplines in Computational Life Sciences, transforming it into a strong helping hand for teachers, students, practitioners and researchers. In Life Sciences, problem-solving and data analysis often depend on biological expertise combined with technical skills in order to generate, manage and efficiently analyse big data. These technical skills can easily be enhanced by good theoretical foundations, developed from well-chosen practical examples and inspiring new strategies. This is the innovative approach of Computational Life Sciences-Data Engineering and Data Mining for Life Sciences: We present basic concepts, advanced topics and emerging technologies, introduce algorithm design and programming principles, address data mining and knowledge discovery as well as applications arising from real projects. Chapters are largely independent and often flanked by illustrative examples and practical advise.

This book constitutes the proceedings of the 18th International Symposium on Bioinformatics Research and Applications, ISBRA 2022, held in Haifa, Israel, in November 14–17, 2022.The 30 full papers and 4 short papers presented in this book were carefully reviewed and selected from 72 submissions. They were organized in topical sections named: AI and disease; computational proteomics; biomedical imaging; drug screening and drug-drug interaction prediction; Biomedical data; sequencing data analysis.

This two-volume set LNCS 14134 and LNCS 14135 constitutes the refereed proceedings of the 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, held in Ponta Delgada, Portugal, during June 19–21, 2023. The 108 full papers presented in this two-volume set were carefully reviewed and selected from 149 submissions. The papers in Part I are organized in topical sections on advanced topics in computational intelligence; advances in artificial neural networks; ANN HW-accelerators; applications of machine learning in biomedicine and healthcare; and applications of machine learning in time series analysis. The papers in Part II are organized in topical sections on deep learning and applications; deep learning applied to computer vision and robotics; general applications of artificial intelligence; interaction with neural systems in both health and disease; machine learning for 4.0 industry solutions; neural networks in chemistry and material characterization; ordinal classification; real world applications of BCI systems; and spiking neural networks: applications and algorithms.

The book contains 35 chapters, in which you can find various examples of the development of methods and/or systems supporting medical diagnostics and therapy, related to biomedical imaging, signal and image processing, biomaterials and artificial organs, modelling of biomedical systems, which were presented as current research topics at the 23rd Polish Biocybernetics and Biomedical Engineering Conference, held at the Institute of Electronics, Lodz University of Technology in September 2023. The ongoing and dynamic development of AI-based data processing and analysis methods plays an increasingly important role in medicine. This book addresses these issues by presenting applications of such methods in various areas, such as disease diagnosis and prediction, particularly through the use of image data analysis algorithms. Other topics covered include personalized medicine, where multimodal patient data is acquired and analyzed, as well as robotic surgery and clinical decision support.The book is of interest to an advanced and broad readership, including researchers and engineers representing both medical, biological, and engineering viewpoints. Its readers may also be graduate and postgraduate students in various fields such as biomedical engineering, artificial intelligence, biomaterials, and medical electronics, as well as software developers in R&D departments working in the field of intelligent healthcare engineering.

This book gathers high-quality research papers presented at the 3rd International Conference on Frontiers in Computing and Systems (COMSYS 2022) held at Indian Institute of Technology Ropar, Punjab, India, during December 19–21, 2022. The book covers research in “cyber-physical systems for real-life applications” pertaining to AI, machine learning, and data science; devices, circuits, and systems; computational biology, biomedical informatics and network medicine; communication networks, cloud computing and IoT; image, video and signal processing; and security and privacy.

This book aims to promote the interaction among the scientific community to discuss applications of CS/AI with an interdisciplinary character, exploring the interactions between sub-areas of CS/AI, bioinformatics, chemoinformatics, and systems biology. The success of bioinformatics in recent years has been prompted by research in molecular biology and molecular medicine in several initiatives. This year's technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research. The PACBB'23 technical program has selected 9 full papers in the main track and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the LASI and Centro Algoritmi of the University of Minho (Portugal). The authors would like to thank all the contributing authors, the members of the program committee, national associations (AEPIA, APPIA), and the sponsors (AIR Institute).

This book presents a collection of high-quality research papers, presented at the Second International Symposium on Bioinformatics and Biomedicine (BioInfoMed'2022). It offers a comprehensive look into some of the fastest growing fields of science, such as biomedicine, bioinformatics, artificial intelligence, and mathematical modeling. The different chapters of the work include both practical solutions and strictly scientific considerations expanding knowledge about the future bioinformatics and biomedical engineering challenges. We believe that the presented works will have a great impact not only on the development and the application of new methods for modeling, decision making and data mining in healthcare and biomedicine, but also it will provide a source of inspiration for researchers who can implement the proposed methods into their practice and scientific studies.

This book constitutes revised selected papers from the 17th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2021, which was held virtually during November 15–17, 2021. The 19 papers included in these proceedings were carefully reviewed and selected from 26 submissions, and they focus on bioinformatics, computational biology, health informatics, cheminformatics, biotechnology, biostatistics, and biomedical imaging.

This book covers recent trends and applications of nonlinear dynamics in various branches of society, science, and engineering. The selected peer-reviewed contributions were presented at the International Conference on Nonlinear Dynamics and Applications (ICNDA 2022) at Sikkim Manipal Institute of Technology (SMIT) and cover a broad swath of topics ranging from chaos theory and fractals to quantum systems and the dynamics of the COVID-19 pandemic. Organized by the SMIT Department of Mathematics, this international conference offers an interdisciplinary stage for scientists, researchers, and inventors to present and discuss the latest innovations and trends in all possible areas of nonlinear dynamics.

This book constitutes the refereed proceedings of the 10th International Workshop on Biomedical Image Registration, WBIR 2020, which was supposed to be held in Munich, Germany, in July 2022.The 11 full and poster papers together with 17 short papers included in this volume were carefully reviewed and selected from 32 submitted papers. The papers are organized in the following topical sections: optimization, deep learning architectures, neuroimaging, diffeomorphisms, uncertainty, topology and metrics.

This book constitutes the proceedings of the 15th Brazilian Symposium on Bioinformatics on Advances in Bioinformatics and Computational Biology, BSB 2022, which took place in Buzios, Brazil, in September 2022. The 10 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 23 submissions. The papers focus on bioinformatics, computational biology, Biological Databases, Biological Networks, Cheminformatics, Evolutionary Genomics, Computational Proteomics, Systems Biology, Drug Design, Genomics, Machine Learning applications in Bioinformatics, Metagenomics, Molecular Docking and Modeling, Molecular Evolution and Phylogenetics, Protein Structure and Modeling, Proteomics, Transcriptomics, Single-Cell Analysis, Workflows in Bioinformatics.

This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The 48 full papers presented in this volume were carefully reviewed and selected from 64 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

This book constitutes the refereed joint proceedings of the 5th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2022, held in September 2022, in conjunction with the 25th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2022.The 10 full papers presented at iMIMIC 2022 were carefully reviewed and selected from 24 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention.

This book includes selected papers from the 5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC 2021), held in Coimbatore, India, during November 25–26, 2021. This book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization and big data modeling and management that make use of effectual computing processes in the bio-inspired systems. It also contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.

This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control. The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design ofhybrid algorithms for applications in data analytics, classification model, and engineering control.

The book presents the results of studies on selected problems (such as predictive model of transcription initiation and termination, protein recognition codes, protein structure prediction, feature selection for disease prediction, information retrieval from medical imaging) of Bioinformatics and Information Retrieval. Information Retrieval is one of the contemporary answers to new challenges in threat evaluation of composite systems. This book provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. It describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook, from basic principles. It presents walk-throughs of data analysis tasks using different tools to help in taking decisions in healthcare management.

This book gives an overview of applications of Machine Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences. Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine. This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which forms a major domain of research in the field of biology. It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.

The book, Transformation in Healthcare with Emerging Technologies, presents healthcare industrial revolution based on service aggregation and virtualisation that can transform the healthcare sector with the aid of technologies such as Artificial Intelligence (AI), Internet of Things (IoT), Bigdata and Blockchain. These technologies offer fast communication between doctors and patients, protected transactions, safe data storage and analysis, immutable data records, transparent data flow service, transaction validation process, and secure data exchanges between organizations. Features: • Discusses the Integration of AI, IoT, big data and blockchain in healthcare industry • Highlights the security and privacy aspect of AI, IoT, big data and blockchain in healthcare industry • Talks about challenges and issues of AI, IoT, big data and blockchain in healthcare industry • Includes several case studies It is primarily aimed at graduates and researchers in computer science and IT who are doing collaborative research with the medical industry. Industry professionals will also find it useful.

This book presents best selected research papers presented at the 4th International Conference on Cognitive Informatics and Soft Computing (CISC 2021), held at Balasore College of Engineering & Technology, Balasore, Odisha, India, from 21–22 August 2021. It highlights, in particular, innovative research in the fields of cognitive informatics, cognitive computing, computational intelligence, advanced computing, and hybrid intelligent models and applications. New algorithms and methods in a variety of fields are presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of computer science, artificial intelligence, cybernetics, automation control theory, and software engineering.

This book encapsulates and occupies recent advances and state-of-the-art applications of nature-inspired computing (NIC) techniques in the field of bioinformatics and computational biology, which would aid medical sciences in various clinical applications. This edited volume covers fundamental applications, scope, and future perspectives of NIC techniques in bioinformatics including genomic profiling, gene expression data classification, DNA computation, systems and network biology, solving personalized therapy complications, antimicrobial resistance in bacterial pathogens, and computer-aided drug design, discovery, and therapeutics. It also covers the role of NIC techniques in various diseases and disorders, including cancer detection and diagnosis, breast cancer, lung disorder detection, disease biomarkers, and potential therapeutics identifications.

This book constitutes the refereed proceedings of the 20th International Conference on Computational Methods in Systems Biology, CMSB 2022, held in Bucharest, Romania, in September 2022.The 13 full papers and 4 tool papers were carefully reviewed and selected from 43 submissions. CMSB focuses on modeling, simulation, analysis, design and control of biological systems. The papers are arranged thematically as follows: Chemical reaction networks; Boolean networks; continuous and hybrid models; machine learning; software.

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists.Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

This book gathers outstanding research papers presented at the 2nd International Conference on Frontiers in Computing and Systems (COMSYS 2021), organized by Department of Electronics and Communication Engineering and Department of Information Technology, North-Eastern Hill University, Shillong, Meghalaya, India held during September 29–October 1, 2021. The book presents the latest research and results in various fields of machine learning, computational intelligence, VLSI, networks and systems, computational biology, and security, making it a rich source of reference material for academia and industry alike.

BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician's important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.

This book presents best selected research papers presented at the 3rd International Conference on Cognitive Informatics and Soft Computing (CISC 2020), held at Balasore College of Engineering & Technology, Balasore, Odisha, India, from 12 to 13 December 2020. It highlights, in particular, innovative research in the fields of cognitive informatics, cognitive computing, computational intelligence, advanced computing, and hybrid intelligent models and applications. New algorithms and methods in a variety of fields are presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of computer science, artificial intelligence, cybernetics, automation control theory, and software engineering.

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and manyothers.

This book constitutes the First 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The challenge took place virtually due to the COVID-19 pandemic.The 2 full and 8 short papers presented together with an overview paper in this volume were carefully reviewed and selected form numerous submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 204 delineated PET/CT images was made available for training as well as 53 PET/CT images for testing. Various deep learning methods were developed by the participants with excellent results.

The emerging biotechnologies have significantly advanced the study of biological mechanisms. However, biological data usually contain a great amount of missing information, e.g. missing features, missing labels or missing samples, which greatly limits the extensive usage of the data. In this book, we introduce different types of biological data missing scenarios and propose machine learning models to improve the data analysis, including deep recurrent neural network recovery for feature missings, robust information theoretic learning for label missings and structure-aware rebalancing for minor sample missings. Models in the book cover the fields of imbalance learning, deep learning, recurrent neural network and statistical inference, providing a wide range of references of the integration between artificial intelligence and biology. With simulated and biological datasets, we apply approaches to a variety of biological tasks, including single-cell characterization, genome-wide association studies, medical image segmentations, and quantify the performances in a number of successful metrics.The outline of this book is as follows. In Chapter 2, we introduce the statistical recovery of missing data features; in Chapter 3, we introduce the statistical recovery of missing labels; in Chapter 4, we introduce the statistical recovery of missing data sample information; finally, in Chapter 5, we summarize the full text and outlook future directions. This book can be used as references for researchers in computational biology, bioinformatics and biostatistics. Readers are expected to have basic knowledge of statistics and machine learning.