Download or read book Applying Machine Learning to Breast Cancer Gene Expression Data to Predict Survival Likelihood written by Pegah Tavangar and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing the expression level of thousands of genes will provide additional information beneficial in improving cancer therapy or synthesizing a new drug. In this project, the expression of 48807 genes from primary human breast tumors cells was analyzed. Humans cannot make sense of such a large volume of gene expression data from each person. Therefore, we used Machine Learning as an automated system that can learn from the data and be able to predict results from the data. This project presents the use of Machine Learning to predict the likelihood of survival in breast cancer patients using gene expression profiling. Machine Learning techniques, such as Logistic Regression, Support Vector Machines, Random Forest, and different Feature Selection techniques were used to find essential genes that lead to breast cancer or help a patient to live longer. This project describes the evaluation of different Machine Learning algorithms to classify breast cancer tumors into two groups of high and low survival.
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 202 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.
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.
Download or read book Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems written by E. Priya and published by Springer Nature. This book was released on 2020-09-21 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
Download or read book Application of Bioinformatics in Cancers written by Chad Brenner and published by MDPI. This book was released on 2019-11-20 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible. Accordingly, the series presented here bring forward a wide range of artificial intelligence approaches and statistical methods that can be applied to imaging and genomics data sets to identify previously unrecognized features that are critical for cancer. Our hope is that these articles will serve as a foundation for future research as the field of cancer biology transitions to integrating electronic health record, imaging, genomics and other complex datasets in order to develop new strategies that improve the overall health of individual patients.
Download or read book High Risk Cutaneous Squamous Cell Carcinoma written by Chrysalyne D. Schmults and published by Springer. This book was released on 2016-04-29 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a cutting-edge resource that provides clinicians with the up-to-date practical knowledge required in order to manage SCC patients optimally. It summarizes newly available information relating to the definition of high-risk SCC, its pathophysiologic underpinnings, and its management. New prognostic information and staging systems are summarized that enable high-risk tumors to be defined more precisely than ever before. Many helpful tips are provided on the practical management of challenging cases, including multiple tumors/field cancerization, high-risk tumors, nodal metastases, and unresectable disease. The authors are all acknowledged experts in the emerging field of high-risk and advanced SCC.
Download or read book Omics for Personalized Medicine written by Debmalya Barh and published by Springer Science & Business Media. This book was released on 2013-10-14 with total page 825 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Omics for Personalized Medicine” will give to its prospective readers the insight of both the current developments and the future potential of personalized medicine. The book brings into light how the pharmacogenomics and omics technologies are bringing a revolution in transforming the medicine and the health care sector for the better. Students of biomedical research and medicine along with medical professionals will benefit tremendously from the book by gaining from the diverse fields of knowledge of new age personalized medicine presented in the highly detailed chapters of the book. The book chapters are divided into two sections for convenient reading with the first section covering the general aspects of pharmaocogenomic technology that includes latest research and development in omics technologies. The first section also highlights the role of omics in modern clinical trials and even discusses the ethical consideration in pharmocogenomics. The second section is focusing on the development of personalized medicine in several areas of human health. The topics covered range from metabolic and neurological disorders to non-communicable as well as infectious diseases, and even explores the role of pharmacogenomics in cell therapy and transplantation technology. Thirty-four chapters of the book cover several aspects of pharmacogenomics and personalized medicine and have taken into consideration the varied interest of the readers from different fields of biomedical research and medicine. Advent of pharmacogenomics is the future of modern medicine, which has resulted from culmination of decades of research and now is showing the way forward. The book is an honest endeavour of researchers from all over the world to disseminate the latest knowledge and knowhow in personalized medicine to the community health researchers in particular and the educated public in general.
Download or read book 2019 22nd International Multitopic Conference INMIC written by IEEE Staff and published by . This book was released on 2019-11-29 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: INMIC 2019 shall be 22nd conference of the series This is the largest computer science and engineering conference in Pakistan and is jointly managed by IEEE Islamabad Section, IEEE Lahore Section and IEEE Karachi Section on rotation basis The conference provides a platform for largest gathering of researchers, academics, professionals and students from engineering and computing domains The conference plays a vital role in promoting research in Pakistan and is one of the most visible IEEE events in Pakistan The conference targets a wide range of areas including software engineering, Computer science, computer vision, image processing, power and control systems, mission and safety critical systems, robotics, communication systems, information security, etc
Download or read book Data Classification written by Charu C. Aggarwal and published by CRC Press. This book was released on 2014-07-25 with total page 710 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains, including text, multimedia, social network, and biological data. This comprehensive book focuses on three primary aspects of data classification: Methods-The book first describes common techniques used for classification, including probabilistic methods, decision trees, rule-based methods, instance-based methods, support vector machine methods, and neural networks. Domains-The book then examines specific methods used for data domains such as multimedia, text, time-series, network, discrete sequence, and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. Variations-The book concludes with insight on variations of the classification process. It discusses ensembles, rare-class learning, distance function learning, active learning, visual learning, transfer learning, and semi-supervised learning as well as evaluation aspects of classifiers.
Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Download or read book Machine Learning in Radiation Oncology written by Issam El Naqa and published by Springer. This book was released on 2015-06-19 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.
Download or read book Data Management Analytics and Innovation written by Neha Sharma and published by Springer Nature. This book was released on 2020-08-18 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17–19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Download or read book Deep Learning in Healthcare written by Yen-Wei Chen and published by Springer Nature. This book was released on 2019-11-18 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
Download or read book Data Mining written by Ian H. Witten and published by Morgan Kaufmann. This book was released on 2000 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively illustrated, this book is ideal for anyone involved at any level in the work of extracting usable knowledge from large collections of data. Complementing the book's instruction is fully functional machine learning software.
Download or read book Artificial Intelligence in Behavioral and Mental Health Care written by David D. Luxton and published by Academic Press. This book was released on 2015-09-10 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. Summarizes AI advances for use in mental health practice Includes advances in AI based decision-making and consultation Describes AI applications for assessment and treatment Details AI advances in robots for clinical settings Provides empirical data on clinical efficacy Explores practical issues of use in clinical settings
Download or read book Cancer Patient Survival written by National Cancer Institute (U.S.) and published by . This book was released on 1976 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Intelligence written by and published by BoD – Books on Demand. This book was released on 2019-07-31 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is taking on an increasingly important role in our society today. In the early days, machines fulfilled only manual activities. Nowadays, these machines extend their capabilities to cognitive tasks as well. And now AI is poised to make a huge contribution to medical and biological applications. From medical equipment to diagnosing and predicting disease to image and video processing, among others, AI has proven to be an area with great potential. The ability of AI to make informed decisions, learn and perceive the environment, and predict certain behavior, among its many other skills, makes this application of paramount importance in today's world. This book discusses and examines AI applications in medicine and biology as well as challenges and opportunities in this fascinating area.
