Data Mining And Machine Learning For Biomedical Applications
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Data Mining And Machine Learning For Biomedical Applications
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Author : Erin Teeple
language : en
Publisher: Academic Press
Release Date : 2022-03-15
Data Mining And Machine Learning For Biomedical Applications written by Erin Teeple and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-15 with Technology & Engineering categories.
Data Mining and Machine Learning for Biomedical Applications is a rigorous practical introduction to the fundamentals of data science. It discusses topics such as data integration and management; statistical methods of data science; methodological approaches used for data mining and knowledge discovery with biomedical domain examples; the core principles and methods of hypothesis-driven statistical analyses; differences and relative benefits of machine learning approaches; predictive model performance assessment; and concepts of bias and variance with respect to the design and evaluation of predictive models. A final chapter presents considerations and limitations when applying and interpreting data science models in biological science and bioengineering. For graduate students, this book offers a comprehensive methods introduction, making it ideal to accompany a course in this area. It is also useful for established engineers and scientists who wish to explore data mining or predictive analytics within their domains of expertise. This reference is fully supported with exercises, discussion questions, code vignettes, and code files with demonstration code. This presentation of coded solutions has been prepared with readers in mind who have limited coding experience. The fully coded methods are presented in both R and Python. The foundational principles covered in this book can be applied by readers when creating new tools for diagnosis, monitoring, information visualization, and robotic intervention. A unique and foundational resource that offers a mastery of foundational concepts and skills for data management and analysis Presents statistical concepts with examples and exercises for a biomedical engineering audience Introduces the underlying principles, conceptual differences, and limitations of statistical learning approaches
Data Mining For Biomedical Applications
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Author : Jinyan Li
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-03-23
Data Mining For Biomedical Applications written by Jinyan Li and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-23 with Computers categories.
This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with one keynote talk were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections
Predictive Modeling In Biomedical Data Mining And Analysis
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Author : Sudipta Roy
language : en
Publisher: Academic Press
Release Date : 2022-08-28
Predictive Modeling In Biomedical Data Mining And Analysis written by Sudipta Roy and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-28 with Science categories.
Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference. Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information. Includes predictive modeling algorithms for both Supervised Learning and Unsupervised Learning for medical diagnosis, data summarization and pattern identification Offers complete coverage of predictive modeling in biomedical applications, including data visualization, information retrieval, data mining, image pre-processing and segmentation, mathematical models and deep neural networks Provides readers with leading-edge coverage of biomedical data processing, including high dimension data, data reduction, clinical decision-making, deep machine learning in large data sets, multimodal, multi-task, and transfer learning, as well as machine learning with Internet of Biomedical Things applications
Biomedical Data Mining For Information Retrieval
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Author : Sujata Dash
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-06
Biomedical Data Mining For Information Retrieval written by Sujata Dash and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-06 with Computers categories.
BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.
Deep Learning For Biomedical Applications
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Author : Utku Kose
language : en
Publisher: CRC Press
Release Date : 2021-07-20
Deep Learning For Biomedical Applications written by Utku Kose and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-20 with Technology & Engineering categories.
This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.
Machine Learning For Biomedical Applications
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Author : Maria Deprez
language : en
Publisher: Academic Press
Release Date : 2023-09-12
Machine Learning For Biomedical Applications written by Maria Deprez and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-12 with Computers categories.
Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch presents machine learning techniques most commonly used in a biomedical setting. Avoiding a theoretical perspective, it provides a practical and interactive way of learning where concepts are presented in short descriptions followed by simple examples using biomedical data. Interactive Python notebooks are provided with each chapter to complement the text and aid understanding. Sections cover uses in biomedical applications, practical Python coding skills, mathematical tools that underpin the field, core machine learning methods, deep learning concepts with examples in Keras, and much more. This accessible and interactive introduction to machine learning and data analysis skills is suitable for undergraduates and postgraduates in biomedical engineering, computer science, the biomedical sciences and clinicians. Gives a basic understanding of the most fundamental concepts within machine learning and their role in biomedical data analysis Shows how to apply a range of commonly used machine learning and deep learning techniques in biomedical problems Develops practical computational skills that are needed to manipulate complex biomedical data sets Shows how to design machine learning experiments that address specific problems related to biomedical data
Data Mining For Biomedical Applications
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Author : Jinyan Li
language : en
Publisher:
Release Date : 2006
Data Mining For Biomedical Applications written by Jinyan Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Computational Learning Approaches To Data Analytics In Biomedical Applications
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Author : Khalid Al-Jabery
language : en
Publisher: Academic Press
Release Date : 2019-11-20
Computational Learning Approaches To Data Analytics In Biomedical Applications written by Khalid Al-Jabery and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Technology & Engineering categories.
Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor
Data Mining For Biomedical Applications
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Author : Jinyan Li
language : en
Publisher: Springer
Release Date : 2006-02-28
Data Mining For Biomedical Applications written by Jinyan Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-28 with Computers categories.
This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with one keynote talk were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections
Data Mining And Machine Learning Applications
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Author : Rohit Raja
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-26
Data Mining And Machine Learning Applications written by Rohit Raja and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-26 with Computers categories.
DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.