Download or read book System Design for Epidemics Using Machine Learning and Deep Learning written by G. R. Kanagachidambaresan and published by Springer Nature. This book was released on 2023-02-01 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.

Download or read book Leveraging Artificial Intelligence in Global Epidemics written by Le Gruenwald and published by Academic Press. This book was released on 2021-07-28 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leveraging Artificial Intelligence in Global Epidemics provides readers with a detailed technical description of the role Artificial Intelligence plays in various stages of a disease outbreak, using COVID-19 as a case study. In the fight against epidemics, medical staff are on the front line; but behind the lines the battle is fought by researchers, and data scientists. Artificial Intelligence has been helping researchers with computer modeling and simulation for predictions about disease progression, the overall economic situation, tax incomes and population development. In the same manner, AI can prepare researchers for any emergency situation by backing the medical science. Artificial Intelligence plays a key and cutting-edge role in the preparedness for and dealing with the outbreak of global epidemics. It can help researchers analyze global data about known viruses to predict the patterns of the next pandemic and the impacts it will have. Not only prediction, AI plays an increasingly important role in assessing readiness, early detection, identification of patients, generating recommendations, situation awareness and more. It is up to the right input and the innovative ways by humans to leverage what AI can do. As COVID-19 has grabbed the world and its economy today, an analysis of the COVID-19 outbreak and the global responses and analytics will pay a long way in preparing humanity for such future situations. Provides readers with understanding of how Artificial Intelligence can be applied to the prediction, forecasting, detection, and testing of global epidemics, using COVID-19 and other recent epidemics such as Ebola, Corona viruses, Zika, influenza, Dengue, Chikungaya, and malaria as case studies Includes background material regarding readiness for coping with epidemics, including Machine Learning models for prediction of epidemic outbreaks based on existing data Includes technical coverage of key topics such as generating recommendations to combat outbreaks, genome sequencing, AI-assisted testing, AI-assisted contact tracing, situation awareness and combating disinformation, and the role of Artificial Intelligence and Machine Learning in drug discovery, vaccine development, and drug re-purposing

Download or read book Machine Learning and Artificial Intelligence written by A.J. Tallón-Ballesteros and published by IOS Press. This book was released on 2020-12-15 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning and artificial intelligence are already widely applied to facilitate our daily lives, as well as scientific research, but with the world currently facing a global COVID-19 pandemic, their capacity to provide an important tool to support those searching for a way to combat the novel corona virus has never been more important. This book presents the proceedings of the International Conference on Machine Learning and Intelligent Systems (MLIS 2020), which was due to be held in Seoul, Korea, from 25-28 October 2020, but which was delivered as an online conference on the same dates due to COVID-19 restrictions. MLIS 2020 was the latest in a series of annual conferences that aim to provide a platform for exchanging knowledge about the most recent scientific and technological advances in the field of machine learning and intelligent systems. The annual conference also strengthens links within the scientific community in related research areas. The book contains 53 papers, selected from more than 160 submissions and presented at MLIS 2020. Selection was based on the results of review and scored on: originality, scientific/practical significance, compelling logical reasoning and language. Topics covered include: data mining, image processing, neural networks, human health, natural language processing, video processing, computational intelligence, expert systems, human-computer interaction, deep learning, and robotics. Offering a current overview of research and developments in machine learning and artificial intelligence, the book will be of interest to all those working in the field.

Download or read book Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases written by Rodriguez, Raul Villamarin and published by IGI Global. This book was released on 2024-02-14 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within the context of global health challenges posed by intractable neurodegenerative diseases like Alzheimer's and Parkinson's, the significance of early diagnosis is critical for effective intervention, and scientists continue to discover new methods of detection. However, actual diagnosis goes beyond detection to include a significant analysis of combined data for many cases, which presents a challenge of several complicated calculations. Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases stands as a groundbreaking work at the intersection of artificial intelligence and neuroscience. The book orchestrates a symphony of cutting-edge techniques and progressions in early detection by assembling eminent experts from the domains of deep learning and neurology. Through a harmonious blend of research areas and pragmatic applications, this monumental work charts the transformative course to revolutionize the landscape of early diagnosis and management of neurodegenerative disorders. Within the pages, readers will embark through the intricate landscape of neurodegenerative diseases, the fundamental underpinnings of deep learning, the nuances of neuroimaging data acquisition and preprocessing, the alchemy of feature extraction and representation learning, and the symphony of deep learning models tailored for neurodegenerative disease diagnosis. The book also delves into integrating multimodal data to augment diagnosis, the imperative of rigorously evaluating and validating deep learning models, and the ethical considerations and challenges entwined with deep learning for neurodegenerative diseases.

Download or read book Data Science for COVID 19 Volume 1 written by Utku Kose and published by Academic Press. This book was released on 2021-05-20 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for COVID-19 presents leading-edge research on data science techniques for the detection, mitigation, treatment and elimination of COVID-19. Sections provide an introduction to data science for COVID-19 research, considering past and future pandemics, as well as related Coronavirus variations. Other chapters cover a wide range of Data Science applications concerning COVID-19 research, including Image Analysis and Data Processing, Geoprocessing and tracking, Predictive Systems, Design Cognition, mobile technology, and telemedicine solutions. The book then covers Artificial Intelligence-based solutions, innovative treatment methods, and public safety. Finally, readers will learn about applications of Big Data and new data models for mitigation. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings Provides insights into innovative data-oriented modeling and predictive techniques from COVID-19 researchers Includes real-world feedback and user experiences from physicians and medical staff from around the world on the effectiveness of applied Data Science solutions

Download or read book Artificial Intelligence and Machine Learning for COVID 19 written by Fadi Al-Turjman and published by Springer Nature. This book was released on 2021-02-19 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies.

Download or read book Proceedings of International Conference on Paradigms of Communication Computing and Data Analytics written by Anupam Yadav and published by Springer Nature. This book was released on 2023-11-11 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of selected high-quality research papers presented at International Conference on Paradigms of Communication, Computing and Data Analytics (PCCDA 2023), held at South Asian University, New Delhi, India, during 22–23 April 2023. It discusses cutting-edge research in the areas of advanced computing, communications and data science techniques. The book is a collection of latest research articles in computation algorithm, communication and data sciences, intertwined with each other for efficiency.

Download or read book Handbook of Security and Privacy of AI Enabled Healthcare Systems and Internet of Medical Things written by Agbotiname Lucky Imoize and published by CRC Press. This book was released on 2023-10-25 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions. This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others.

Download or read book Artificial Intelligence for COVID 19 written by Diego Oliva and published by Springer Nature. This book was released on 2021-07-19 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.

Download or read book Impact of AI and Data Science in Response to Coronavirus Pandemic written by Sushruta Mishra and published by Springer Nature. This book was released on 2021-07-22 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies. It provides a unique opportunity to present the work on state-of-the-art of modern artificial intelligence tools and technologies to track and forecast COVID-19 cases. It indicates insights and viewpoints from scholars regarding risk and resilience analytics for policy making and operations of large-scale systems on this epidemic. A snapshot of the latest architectures, frameworks in machine learning and data science are also highlighted to gather and aggregate data records related to COVID-19 and to diagnose the virus. It delivers significant research outcomes and inspiring new real-world applications with respect to feasible AI based solutions in COVID-19 outbreak. In addition, it discusses strong preventive measures to control such pandemic.

Download or read book Automatic Speech Recognition and Translation for Low Resource Languages written by L. Ashok Kumar and published by John Wiley & Sons. This book was released on 2024-03-28 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: AUTOMATIC SPEECH RECOGNITION and TRANSLATION for LOW-RESOURCE LANGUAGES This book is a comprehensive exploration into the cutting-edge research, methodologies, and advancements in addressing the unique challenges associated with ASR and translation for low-resource languages. Automatic Speech Recognition and Translation for Low Resource Languages contains groundbreaking research from experts and researchers sharing innovative solutions that address language challenges in low-resource environments. The book begins by delving into the fundamental concepts of ASR and translation, providing readers with a solid foundation for understanding the subsequent chapters. It then explores the intricacies of low-resource languages, analyzing the factors that contribute to their challenges and the significance of developing tailored solutions to overcome them. The chapters encompass a wide range of topics, ranging from both the theoretical and practical aspects of ASR and translation for low-resource languages. The book discusses data augmentation techniques, transfer learning, and multilingual training approaches that leverage the power of existing linguistic resources to improve accuracy and performance. Additionally, it investigates the possibilities offered by unsupervised and semi-supervised learning, as well as the benefits of active learning and crowdsourcing in enriching the training data. Throughout the book, emphasis is placed on the importance of considering the cultural and linguistic context of low-resource languages, recognizing the unique nuances and intricacies that influence accurate ASR and translation. Furthermore, the book explores the potential impact of these technologies in various domains, such as healthcare, education, and commerce, empowering individuals and communities by breaking down language barriers. Audience The book targets researchers and professionals in the fields of natural language processing, computational linguistics, and speech technology. It will also be of interest to engineers, linguists, and individuals in industries and organizations working on cross-lingual communication, accessibility, and global connectivity.

Download or read book Novel AI and Data Science Advancements for Sustainability in the Era of COVID 19 written by Victor Chang and published by Academic Press. This book was released on 2022-04-05 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 discusses how the role of recent technologies applied to health settings can help fight virus outbreaks. Moreover, it provides guidelines on how governments and institutions should prepare and quickly respond to drastic situations using technology to support their communities in order to maintain life and functional as efficiently as possible. The book discusses topics such as AI-driven histopathology analysis for COVID-19 diagnosis, bioinformatics for subtype rational drug design, deep learning-based treatment evaluation and outcome prediction, sensor informatics for monitoring infected patients, and machine learning for tracking and prediction models. In addition, the book presents AI solutions for hospital management during an epidemic or pandemic, along with real-world solutions and case studies of successful measures to support different types of communities. This is a valuable source for medical informaticians, bioinformaticians, clinicians and other healthcare workers and researchers who are interested in learning more on how recently developed technologies can help us fight and minimize the effects of global pandemics. Discusses AI advancements in predictive and decision modeling and how to design mobile apps to track contagion spread Presents the smart contract concept in blockchain and cryptography technology to guarantee security and privacy of people’s data once their information has been used to fight the pandemic Encompasses guidelines for emergency preparedness, planning, recovery and continuity management of communities to support people in emergencies like a virus outbreak

Download or read book Active Learning to Minimize the Possible Risk of Future Epidemics written by KC Santosh and published by Springer Nature. This book was released on 2023-12-24 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big enough to effectively tackle future epidemics? In this context, active learning, often referred to as human or expert-in-the-loop learning, becomes imperative, enabling machines to commence learning from day one with minimal labeled data. In unsupervised learning, the focus shifts toward constructing advanced machine learning models like deep structured networks that autonomously learn over time, with human or expert intervention only when errors occur and for limited data—a process we term mentoring. In the context of Covid-19, this book explores the use of deep features to classify data into two clusters (0/1: Covid-19/non-Covid-19) across three distinct datasets: cough sound, Computed Tomography (CT) scan, and chest x-ray (CXR). Not to be confused, our primary objective is to provide a strong assertion on how active learning could potentially be used to predict disease from any upcoming epidemics. Upon request (education/training purpose), GitHub source codes are provided.

Download or read book Cyber Physical Systems written by Ramesh Poonia and published by Academic Press. This book was released on 2021-10-30 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture. Offers perspectives on the design, development and commissioning of intelligent applications Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of COVID-19 Puts forth insights on how future illnesses can be supported using intelligent corona virus monitoring techniques

Download or read book Controlling Epidemics With Mathematical and Machine Learning Models written by Varghese, Abraham and published by IGI Global. This book was released on 2022-10-21 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Communicable diseases have been an important part of human history. Epidemics afflicted populations, causing many deaths before gradually fading away and emerging again years after. Epidemics of infectious diseases are occurring more often, and spreading faster and further than ever, in many different regions of the world. The scientific community, in addition to its accelerated efforts to develop an effective treatment and vaccination, is also playing an important role in advising policymakers on possible non-pharmacological approaches to limit the catastrophic impact of epidemics using mathematical and machine learning models. Controlling Epidemics With Mathematical and Machine Learning Models provides mathematical and machine learning models for epidemical diseases, with special attention given to the COVID-19 pandemic. It gives mathematical proof of the stability and size of diseases. Covering topics such as compartmental models, reproduction number, and SIR model simulation, this premier reference source is an essential resource for statisticians, government officials, health professionals, epidemiologists, sociologists, students and educators of higher education, librarians, researchers, and academicians.

Download or read book Intelligent Systems and Methods to Combat Covid 19 written by Amit Joshi and published by Springer Nature. This book was released on 2020-08-26 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.

Download or read book Machine Learning and Data Analytics for Predicting Managing and Monitoring Disease written by Roy, Manikant and published by IGI Global. This book was released on 2021-06-25 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.