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Machine Learning in Bio Signal Analysis and Diagnostic Imaging

Machine Learning in Bio Signal Analysis and Diagnostic Imaging
  • Author : Nilanjan Dey
  • Publsiher : Academic Press
  • Release : 30 November 2018
  • ISBN : 012816087X
  • Pages : 345 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKMachine Learning in Bio Signal Analysis and Diagnostic Imaging

Summary:
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains


Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging
  • Author : Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
  • Publisher : Academic Press
  • Release : 30 November 2018
GET THIS BOOKMachine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as

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Signal Processing and Machine Learning for Biomedical Big Data

Signal Processing and Machine Learning for Biomedical Big Data
  • Author : Ervin Sejdic,Tiago H. Falk
  • Publisher : CRC Press
  • Release : 04 July 2018
GET THIS BOOKSignal Processing and Machine Learning for Biomedical Big Data

This will be a comprehensive, multi-contributed reference work that will detail the latest research and developments in biomedical signal processing related to big data medical analysis. It will describe signal processing, machine learning, and parallel computing strategies to revolutionize the world of medical analytics and diagnosis as presented by world class researchers and experts in this important field. The chapters will desribe tools that can be used by biomedical and clinical practitioners as well as industry professionals. It will give

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Classification and Clustering in Biomedical Signal Processing

Classification and Clustering in Biomedical Signal Processing
  • Author : Dey, Nilanjan
  • Publisher : IGI Global
  • Release : 07 April 2016
GET THIS BOOKClassification and Clustering in Biomedical Signal Processing

Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research

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Bio-inspired Physiological Signal(s) and Medical Image(s) Neural Processing Systems Based on Deep Learning and Mathematical Modeling for Implementing Bio-Engineering Applications in Medical and Industrial Fields


Biomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare
  • Author : Walid A. Zgallai
  • Publisher : Academic Press
  • Release : 29 July 2020
GET THIS BOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of

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Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis

Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis
  • Author : Khalid Raza
  • Publisher : Springer Nature
  • Release : 16 October 2020
GET THIS BOOKComputational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis

The novel coronavirus disease 2019 (COVID-19) pandemic has posed a major threat to human life and health. This book is beneficial for interdisciplinary students, researchers, and professionals to understand COVID-19 and how computational intelligence can be used for the purpose of surveillance, control, prevention, prediction, diagnosis, and potential treatment of the disease. The book contains different aspects of COVID-19 that includes fundamental knowledge, epidemic forecast models, surveillance and tracking systems, IoT- and IoMT-based integrated systems for COVID-19, social network analysis systems

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Advances in Deep Learning for Medical Image Analysis

Advances in Deep Learning for Medical Image Analysis
  • Author : Archana Mire,Vinayak Elangovan,Shailaja Patil
  • Publisher : CRC Press
  • Release : 28 April 2022
GET THIS BOOKAdvances in Deep Learning for Medical Image Analysis

This reference text introduces the classical probabilistic model, deep learning, and big data techniques for improving medical imaging and detecting various diseases. The text addresses a wide variety of application areas in medical imaging where deep learning techniques provide solutions with lesser human intervention and reduced time. It comprehensively covers important machine learning for signal analysis, deep learning techniques for cancer detection, diabetic cases, skin image analysis, Alzheimer’s disease detection, coronary disease detection, medical image forensic, fetal anomaly detection,

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Sensors for Health Monitoring

Sensors for Health Monitoring
  • Author : Nilanjan Dey,Jyotismita Chaki,Rajesh Kumar
  • Publisher : Academic Press
  • Release : 09 September 2019
GET THIS BOOKSensors for Health Monitoring

Sensors for Health Monitoring discusses the characteristics of U-Healthcare systems in different domains, providing a foundation for working professionals and undergraduate and postgraduate students. The book provides information and advice on how to choose the best sensors for a U-Healthcare system, advises and guides readers on how to overcome challenges relating to data acquisition and signal processing, and presents comprehensive coverage of up-to-date requirements in hardware, communication and calculation for next-generation uHealth systems. It then compares new technological and technical

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Advances in Data Computing, Communication and Security

Advances in Data Computing, Communication and Security
  • Author : Pankaj Verma,Chhagan Charan,Xavier Fernando,Subramaniam Ganesan
  • Publisher : Springer Nature
  • Release : 28 March 2022
GET THIS BOOKAdvances in Data Computing, Communication and Security

This book is a collection of high-quality peer reviewed contributions from the academicians, researchers, practitioners, and industry professionals, accepted in the International Conference on Advances in Data Computing, Communication and Security (I3CS2021) organized by the Department of Electronics and Communication Engineering in collaboration with the Department of Computer Engineering, National Institute of Technology, Kurukshetra, India during 08-10 Sep 2021. The fast pace of advancing technologies and growing expectations of the next-generation requires that the researchers must continuously reinvent themselves through

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Machine Learning for Critical Internet of Medical Things

Machine Learning for Critical Internet of Medical Things
  • Author : Fadi Al-Turjman,Anand Nayyar
  • Publisher : Springer Nature
  • Release : 22 May 2022
GET THIS BOOKMachine Learning for Critical Internet of Medical Things

This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and

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Intelligent Decision Support Systems

Intelligent Decision Support Systems
  • Author : Surekha Borra,Nilanjan Dey,Siddhartha Bhattacharyya,Mohamed Salim Bouhlel
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 21 October 2019
GET THIS BOOKIntelligent Decision Support Systems

Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software engineering (SE), knowledge based systems (KBS), data mining, artificial intelligence (AI) and include several systems developed from the study of expert systems (ES), genetic algorithms (GA), artificial neural networks (ANN) and fuzzy-logic systems The use of automatic decision support systems in design and manufacturing industry, healthcare and commercial software development systems has the following benifits: Cost savings in companies, due to employment

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Machine Learning and Medical Imaging

Machine Learning and Medical Imaging
  • Author : Guorong Wu,Dinggang Shen,Mert Sabuncu
  • Publisher : Academic Press
  • Release : 11 August 2016
GET THIS BOOKMachine Learning and Medical Imaging

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging

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Emerging Technologies in Healthcare

Emerging Technologies in Healthcare
  • Author : Matthew N. O. Sadiku,Rotimi A. K. Jaiyesimi,Joyce B. Idehen,Sarhan M. Musa
  • Publisher : AuthorHouse
  • Release : 05 October 2021
GET THIS BOOKEmerging Technologies in Healthcare

Health is regarded as one of the global challenges for mankind. Healthcare is a complex system that covers processes of diagnosis, treatment, and prevention of diseases. It constitutes a fundamental pillar of the modern society. Modern healthcare is technological healthcare. Technology is everywhere. This book focuses on twenty-one emerging technologies in the healthcare industry. An emerging technology is one that holds the promise of creating a new economic engine and is trans-industrial. Emerging technological trends are rapidly transforming businesses in

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Advanced Intelligent Systems for Sustainable Development (AI2SD'2020)

Advanced Intelligent Systems for Sustainable Development (AI2SD'2020)
  • Author : Janusz Kacprzyk
  • Publisher : Springer Nature
  • Release : 22 May 2022
GET THIS BOOKAdvanced Intelligent Systems for Sustainable Development (AI2SD'2020)

This book publishes the best papers accepted and presented at the 3rd edition of the International Conference on Advanced Intelligent Systems for Sustainable Development Applied to Agriculture, Energy, Health, Environment, Industry, Education, Economy, and Security (AI2SD2020). This conference is one of the biggest amalgamations of eminent researchers, students, and delegates from both academia and industry where the collaborators have an interactive access to emerging technology and approaches globally. In this book, readers find the latest ideas addressing technological issues

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