Deep Learning for Cancer Diagnosis

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Publisher : Springer Nature
ISBN 13 : 9811563217
Total Pages : 311 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Deep Learning for Cancer Diagnosis by : Utku Kose

Download or read book Deep Learning for Cancer Diagnosis written by Utku Kose and published by Springer Nature. This book was released on 2020-09-12 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.

Deep Learning for Cancer Diagnosis

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Publisher :
ISBN 13 : 9789811563225
Total Pages : 0 pages
Book Rating : 4.5/5 (632 download)

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Book Synopsis Deep Learning for Cancer Diagnosis by : Utku Kose

Download or read book Deep Learning for Cancer Diagnosis written by Utku Kose and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.

Current Applications of Deep Learning in Cancer Diagnostics

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Publisher : CRC Press
ISBN 13 : 1000836150
Total Pages : 189 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Current Applications of Deep Learning in Cancer Diagnostics by : Jyotismita Chaki

Download or read book Current Applications of Deep Learning in Cancer Diagnostics written by Jyotismita Chaki and published by CRC Press. This book was released on 2023-02-22 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques, which are essential to cancer diagnostics. Topics include introduction to current applications of deep learning in cancer diagnostics, pre-processing of cancer data using deep learning, review of deep learning techniques in oncology, overview of advanced deep learning techniques in cancer diagnostics, prediction of cancer susceptibility using deep learning techniques, prediction of cancer reoccurrence using deep learning techniques, deep learning techniques to predict the grading of human cancer, different human cancer detection using deep learning techniques, prediction of cancer survival using deep learning techniques, complexity in the use of deep learning in cancer diagnostics, and challenges and future scopes of deep learning techniques in oncology.

Deep Learning in Cancer Diagnostics

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Author :
Publisher : Springer Nature
ISBN 13 : 9811989370
Total Pages : 41 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Deep Learning in Cancer Diagnostics by : Mohd Hafiz Arzmi

Download or read book Deep Learning in Cancer Diagnostics written by Mohd Hafiz Arzmi and published by Springer Nature. This book was released on 2023-01-18 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is the leading cause of mortality in most, if not all, countries around the globe. It is worth noting that the World Health Organisation (WHO) in 2019 estimated that cancer is the primary or secondary leading cause of death in 112 of 183 countries for individuals less than 70 years old, which is alarming. In addition, cancer affects socioeconomic development as well. The diagnostics of cancer are often carried out by medical experts through medical imaging; nevertheless, it is not without misdiagnosis owing to a myriad of reasons. With the advancement of technology and computing power, the use of state-of-the-art computational methods for the accurate diagnosis of cancer is no longer far-fetched. In this brief, the diagnosis of four types of common cancers, i.e., breast, lung, oral and skin, are evaluated with different state-of-the-art feature-based transfer learning models. It is expected that the findings in this book are insightful to various stakeholders in the diagnosis of cancer. ​

Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

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Publisher : IGI Global
ISBN 13 : 1799875172
Total Pages : 304 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Examining the Impact of Deep Learning and IoT on Multi-Industry Applications by : Raut, Roshani

Download or read book Examining the Impact of Deep Learning and IoT on Multi-Industry Applications written by Raut, Roshani and published by IGI Global. This book was released on 2021-01-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

Advanced Machine Learning Approaches in Cancer Prognosis

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Publisher : Springer Nature
ISBN 13 : 3030719758
Total Pages : 461 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Advanced Machine Learning Approaches in Cancer Prognosis by : Janmenjoy Nayak

Download or read book Advanced Machine Learning Approaches in Cancer Prognosis written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2021-05-29 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.

Computational Analysis and Deep Learning for Medical Care

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Publisher : John Wiley & Sons
ISBN 13 : 1119785723
Total Pages : 532 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Computational Analysis and Deep Learning for Medical Care by : Amit Kumar Tyagi

Download or read book Computational Analysis and Deep Learning for Medical Care written by Amit Kumar Tyagi and published by John Wiley & Sons. This book was released on 2021-08-24 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.

Artificial Intelligence in Cancer

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Publisher : Academic Press
ISBN 13 : 0128204109
Total Pages : 310 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Artificial Intelligence in Cancer by : Smaranda Belciug

Download or read book Artificial Intelligence in Cancer written by Smaranda Belciug and published by Academic Press. This book was released on 2020-06-18 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Cancer: Diagnostic to Tailored Treatment provides theoretical concepts and practical techniques of AI and its applications in cancer management, building a roadmap on how to use AI in cancer at different stages of healthcare. It discusses topics such as the impactful role of AI during diagnosis and how it can support clinicians to make better decisions, AI tools to help pathologists identify exact types of cancer, how AI supports tumor profiling and can assist surgeons, and the gains in precision for oncologists using AI tools. Additionally, it provides information on AI used for survival and remission/recurrence analysis. The book is a valuable source for bioinformaticians, cancer researchers, oncologists, clinicians and members of the biomedical field who want to understand the promising field of AI applications in cancer management. Discusses over 20 real cancer examples, bringing state-of-the-art cancer cases in which AI was used to help the medical personnel Presents over 100 diagrams, making it easier to comprehend AI’s results on a specific problem through visual resources Explains AI algorithms in a friendly manner, thus helping the reader implement or use them in a specific cancer case

Cancer Prediction for Industrial IoT 4.0

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Publisher : CRC Press
ISBN 13 : 1000508587
Total Pages : 217 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 2021-12-31 with total page 217 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.

Machine Learning with Health Care Perspective

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Publisher : Springer Nature
ISBN 13 : 3030408507
Total Pages : 418 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning with Health Care Perspective by : Vishal Jain

Download or read book Machine Learning with Health Care Perspective written by Vishal Jain and published by Springer Nature. This book was released on 2020-03-09 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.

Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management

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Publisher : CRC Press
ISBN 13 : 1420036386
Total Pages : 216 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management by : R. N. G. Naguib

Download or read book Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management written by R. N. G. Naguib and published by CRC Press. This book was released on 2001-06-22 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: The potential value of artificial neural networks (ANN) as a predictor of malignancy has begun to receive increased recognition. Research and case studies can be found scattered throughout a multitude of journals. Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management brings together the work of top researchers - primaril

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

Emerging Technologies for Healthcare

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Publisher : John Wiley & Sons
ISBN 13 : 1119791723
Total Pages : 418 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Emerging Technologies for Healthcare by : Monika Mangla

Download or read book Emerging Technologies for Healthcare written by Monika Mangla and published by John Wiley & Sons. This book was released on 2021-08-17 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Emerging Technologies for Healthcare” begins with an IoT-based solution for the automated healthcare sector which is enhanced to provide solutions with advanced deep learning techniques. The book provides feasible solutions through various machine learning approaches and applies them to disease analysis and prediction. An example of this is employing a three-dimensional matrix approach for treating chronic kidney disease, the diagnosis and prognostication of acquired demyelinating syndrome (ADS) and autism spectrum disorder, and the detection of pneumonia. In addition, it provides healthcare solutions for post COVID-19 outbreaks through various suitable approaches, Moreover, a detailed detection mechanism is discussed which is used to devise solutions for predicting personality through handwriting recognition; and novel approaches for sentiment analysis are also discussed with sufficient data and its dimensions. This book not only covers theoretical approaches and algorithms, but also contains the sequence of steps used to analyze problems with data, processes, reports, and optimization techniques. It will serve as a single source for solving various problems via machine learning algorithms.

Recent Advances in Cancer Diagnostics and Therapy

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Publisher : CRC Press
ISBN 13 : 1000528138
Total Pages : 233 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Recent Advances in Cancer Diagnostics and Therapy by : Anjana Pandey

Download or read book Recent Advances in Cancer Diagnostics and Therapy written by Anjana Pandey and published by CRC Press. This book was released on 2022-01-18 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides information about different types and stages of cancer and their subtypes with their respective molecular mechanisms, etiology, histopathology, and cellular origins. This book also provides detailed information about cancer incidence, mortality, and different types of technologies both bio and nano employed in cancer diagnosis and screening, and their applications in cancer therapies. This book informs readers about molecular mechanisms of cancer, diagnosis, and therapies along with different computational techniques used on a single platform. The chapters include a broad and integrated perspective on cancer-related topics. This book covers both conventional and emerging techniques employed in cancer screening and diagnosis, including imaging, biomarker, and electrochemical nanosensor-based approaches with detailed information on sensor development. Similarly, this book also covers the mechanisms of different conventional and emerging herbal and nano therapies used in cancer treatment. The authors discuss applications of different computational and mathematical tools, such as machine-learning methods, that can be employed in cancer diagnosis and therapy at the level of personalized medicine. Features: Offers an integrated approach to provide information about all aspects of cancer biology, diagnosis, and therapy Focuses on both conventional and emerging tools/techniques applicable in cancer screening and diagnosis Covers the mechanisms of conventional and emerging anticancer drugs and therapies Provides insights about a personalized medicine-based approach in cancer diagnosis and therapy This book is essential for university students, course lecturers, researchers, and industrialists working in the fields of cancer biology, medicine, and pharmacology.

Biomedical Computing for Breast Cancer Detection and Diagnosis

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Publisher : IGI Global
ISBN 13 : 1799834573
Total Pages : 357 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Biomedical Computing for Breast Cancer Detection and Diagnosis by : Pinheiro dos Santos, Wellington

Download or read book Biomedical Computing for Breast Cancer Detection and Diagnosis written by Pinheiro dos Santos, Wellington and published by IGI Global. This book was released on 2020-07-17 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite success with treatment when diagnosed early, breast cancer is still one of the most fatal forms of cancer for women. Imaging diagnosis is still one of the most efficient ways to detect early breast changes with mammography among the most used techniques. However, there are other techniques that have emerged as alternatives or even complementary tests in the early detection of breast lesions (e.g., breast thermography and electrical impedance tomography). Artificial intelligence can be used to optimize image diagnosis, increasing the reliability of the reports and supporting professionals who do not have enough knowledge or experience to make good diagnoses. Biomedical Computing for Breast Cancer Detection and Diagnosis is a collection of research that presents a review of the physiology and anatomy of the breast; the dynamics of breast cancer; principles of pattern recognition, artificial neural networks, and computer graphics; and the breast imaging techniques and computational methods to support and optimize the diagnosis. While highlighting topics including mammograms, thermographic imaging, and intelligent systems, this book is ideally designed for medical oncologists, surgeons, biomedical engineers, medical imaging professionals, cancer researchers, academicians, and students in medicine, biomedicine, biomedical engineering, and computer science.

Data Analytics in Bioinformatics

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Publisher : John Wiley & Sons
ISBN 13 : 111978560X
Total Pages : 433 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 433 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.

Applied Smart Health Care Informatics

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Publisher : John Wiley & Sons
ISBN 13 : 1119743176
Total Pages : 228 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Applied Smart Health Care Informatics by : Sourav De

Download or read book Applied Smart Health Care Informatics written by Sourav De and published by John Wiley & Sons. This book was released on 2022-03-07 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Smart Health Care Informatics Explores how intelligent systems offer new opportunities for optimizing the acquisition, storage, retrieval, and use of information in healthcare Applied Smart Health Care Informatics explores how health information technology and intelligent systems can be integrated and deployed to enhance healthcare management. Edited and authored by leading experts in the field, this timely volume introduces modern approaches for managing existing data in the healthcare sector by utilizing artificial intelligence (AI), meta-heuristic algorithms, deep learning, the Internet of Things (IoT), and other smart technologies. Detailed chapters review advances in areas including machine learning, computer vision, and soft computing techniques, and discuss various applications of healthcare management systems such as medical imaging, electronic medical records (EMR), and drug development assistance. Throughout the text, the authors propose new research directions and highlight the smart technologies that are central to establishing proactive health management, supporting enhanced coordination of care, and improving the overall quality of healthcare services. Provides an overview of different deep learning applications for intelligent healthcare informatics management Describes novel methodologies and emerging trends in artificial intelligence and computational intelligence and their relevance to health information engineering and management Proposes IoT solutions that disseminate essential medical information for intelligent healthcare management Discusses mobile-based healthcare management, content-based image retrieval, and computer-aided diagnosis using machine and deep learning techniques Examines the use of exploratory data analysis in intelligent healthcare informatics systems Applied Smart Health Care Informatics: A Computational Intelligence Perspective is an invaluable text for graduate students, postdoctoral researchers, academic lecturers, and industry professionals working in the area of healthcare and intelligent soft computing.