Ai Driven Alzheimer S Disease Detection And Prediction

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Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications

Author : Khang, Alex
Publisher : IGI Global
Page : 332 pages
File Size : 40,6 Mb
Release : 2024-02-26
Category : Medical
ISBN : 9798369336809

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Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications by Khang, Alex Pdf

Academic scholars face the daunting challenge of keeping pace with the rapid evolution of innovative technologies. The emergence of AI-driven solutions, deep learning frameworks, and medical robotics introduces a complex terrain, demanding in-depth understanding and analysis. As scholars navigate the intricacies of patient hate speech detection, cardiovascular diseases AI-CDSS, and the revolution in medical diagnostics, a pressing need arises for comprehensive insights that bridge the gap between theoretical knowledge and practical applications. Driving Smart Medical Diagnosis Through AI-Powered Technologies and Applications serves as a solution in this era of transformative healthcare and addresses these challenges head-on. It unravels the complexities surrounding the implementation of AI in healthcare, offering in-depth discussions on the latest breakthroughs. From unraveling the mysteries of AI-driven cataract detection to exploring the implications of decentralized mammography classification, the book is a valuable resource that equips scholars with the knowledge to navigate this innovative landscape.

Using Traditional Design Methods to Enhance AI-Driven Decision Making

Author : Nguyen, Tien V. T.,Vo, Nhut T. M.
Publisher : IGI Global
Page : 528 pages
File Size : 46,6 Mb
Release : 2024-01-10
Category : Computers
ISBN : 9798369306406

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Using Traditional Design Methods to Enhance AI-Driven Decision Making by Nguyen, Tien V. T.,Vo, Nhut T. M. Pdf

In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.

Artificial Intelligence in Healthcare

Author : Adam Bohr,Kaveh Memarzadeh
Publisher : Academic Press
Page : 385 pages
File Size : 44,5 Mb
Release : 2020-06-21
Category : Computers
ISBN : 9780128184394

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Artificial Intelligence in Healthcare by Adam Bohr,Kaveh Memarzadeh Pdf

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Artificial Intelligence and Big Data Analytics for Smart Healthcare

Author : Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui
Publisher : Academic Press
Page : 292 pages
File Size : 48,7 Mb
Release : 2021-10-22
Category : Medical
ISBN : 9780128220627

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Artificial Intelligence and Big Data Analytics for Smart Healthcare by Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui Pdf

Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers

Handbook of Decision Support Systems for Neurological Disorders

Author : D. Jude Hemanth
Publisher : Elsevier
Page : 320 pages
File Size : 55,8 Mb
Release : 2021-04-07
Category : Science
ISBN : 9780128222713

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Handbook of Decision Support Systems for Neurological Disorders by D. Jude Hemanth Pdf

Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided diagnosis systems for neurological disorders. While computer-aided decision support systems for different medical imaging modalities are available, this is the first book to solely concentrate on decision support systems for neurological disorders. Due to the increase in the prevalence of diseases such as Alzheimer, Parkinson's and Dementia, this book will have significant importance in the medical field. Topics discussed include recent computational approaches, different types of neurological disorders, deep convolution neural networks, generative adversarial networks, auto encoders, recurrent neural networks, and modified/hybrid artificial neural networks. Includes applications of computer intelligence and decision support systems for the diagnosis and analysis of a variety of neurological disorders Presents in-depth, technical coverage of computer-aided systems for tumor image classification, Alzheimer's disease detection, dementia detection using deep belief neural networks, and morphological approaches for stroke detection Covers disease diagnosis for cerebral palsy using auto-encoder approaches, contrast enhancement for performance enhanced diagnosis systems, autism detection using fuzzy logic systems, and autism detection using generative adversarial networks Written by engineers to help engineers, computer scientists, researchers and clinicians understand the technology and applications of decision support systems for neurological disorders

Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods

Author : Lilhore, Umesh Kumar,Kumar, Abhishek,Simaiya, Sarita,Vyas, Narayan,Dutt, Vishal
Publisher : IGI Global
Page : 418 pages
File Size : 49,7 Mb
Release : 2024-03-22
Category : Computers
ISBN : 9798369318232

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Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods by Lilhore, Umesh Kumar,Kumar, Abhishek,Simaiya, Sarita,Vyas, Narayan,Dutt, Vishal Pdf

Why are cutting-edge data science techniques such as bioinformatics, few-shot learning, and zero-shot learning underutilized in the world of biological sciences?. In a rapidly advancing field, the failure to harness the full potential of these disciplines limits scientistsÂ’ ability to unlock critical insights into biological systems, personalized medicine, and biomarker identification. This untapped potential hinders progress and limits our capacity to tackle complex biological challenges. The solution to this issue lies within the pages of Applying Machine Learning Techniques to Bioinformatics. This book serves as a powerful resource, offering a comprehensive analysis of how these emerging disciplines can be effectively applied to the realm of biological research. By addressing these challenges and providing in-depth case studies and practical implementations, the book equips researchers, scientists, and curious minds with the knowledge and techniques needed to navigate the ever-changing landscape of bioinformatics and machine learning within the biological sciences.

AI for Disease Surveillance and Pandemic Intelligence

Author : Arash Shaban-Nejad,Martin Michalowski,Simone Bianco
Publisher : Springer Nature
Page : 335 pages
File Size : 51,6 Mb
Release : 2022-03-08
Category : Technology & Engineering
ISBN : 9783030930806

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AI for Disease Surveillance and Pandemic Intelligence by Arash Shaban-Nejad,Martin Michalowski,Simone Bianco Pdf

This book aims to highlight the latest achievements in the use of artificial intelligence for digital disease surveillance, pandemic intelligence, as well as public and clinical health surveillance. The edited book contains selected papers presented at the 2021 Health Intelligence workshop, co-located with the Association for the Advancement of Artificial Intelligence (AAAI) annual conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. While disease surveillance has always been a crucial process, the recent global health crisis caused by COVID-19 has once again highlighted our dependence on intelligent surveillance infrastructures that provide support for making sound and timely decisions. This book provides information for researchers, students, industry professionals, and public health agencies interested in the applications of AI in population health and personalized medicine.

Artificial Intelligence and Machine Learning in Drug Design and Development

Author : Abhirup Khanna,May El Barachi,Sapna Jain,Manoj Kumar,Anand Nayyar
Publisher : John Wiley & Sons
Page : 677 pages
File Size : 43,8 Mb
Release : 2024-07-18
Category : Computers
ISBN : 9781394234165

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Artificial Intelligence and Machine Learning in Drug Design and Development by Abhirup Khanna,May El Barachi,Sapna Jain,Manoj Kumar,Anand Nayyar Pdf

The book is a comprehensive guide that explores the use of artificial intelligence and machine learning in drug discovery and development covering a range of topics, including the use of molecular modeling, docking, identifying targets, selecting compounds, and optimizing drugs. The intersection of Artificial Intelligence (AI) and Machine Learning (ML) within the field of drug design and development represents a pivotal moment in the history of healthcare and pharmaceuticals. The remarkable synergy between cutting-edge technology and the life sciences has ushered in a new era of possibilities, offering unprecedented opportunities, formidable challenges, and a tantalizing glimpse into the future of medicine. AI can be applied to all the key areas of the pharmaceutical industry, such as drug discovery and development, drug repurposing, and improving productivity within a short period. Contemporary methods have shown promising results in facilitating the discovery of drugs to target different diseases. Moreover, AI helps in predicting the efficacy and safety of molecules and gives researchers a much broader chemical pallet for the selection of the best molecules for drug testing and delivery. In this context, drug repurposing is another important topic where AI can have a substantial impact. With the vast amount of clinical and pharmaceutical data available to date, AI algorithms find suitable drugs that can be repurposed for alternative use in medicine. This book is a comprehensive exploration of this dynamic and rapidly evolving field. In an era where precision and efficiency are paramount in drug discovery, AI and ML have emerged as transformative tools, reshaping the way we identify, design, and develop pharmaceuticals. This book is a testament to the profound impact these technologies have had and will continue to have on the pharmaceutical industry, healthcare, and ultimately, patient well-being. The editors of this volume have assembled a distinguished group of experts, researchers, and thought leaders from both the AI, ML, and pharmaceutical domains. Their collective knowledge and insights illuminate the multifaceted landscape of AI and ML in drug design and development, offering a roadmap for navigating its complexities and harnessing its potential. In each section, readers will find a rich tapestry of knowledge, case studies, and expert opinions, providing a 360-degree view of AI and ML’s role in drug design and development. Whether you are a researcher, scientist, industry professional, policymaker, or simply curious about the future of medicine, this book offers 19 state-of-the-art chapters providing valuable insights and a compass to navigate the exciting journey ahead. Audience The book is a valuable resource for a wide range of professionals in the pharmaceutical and allied industries including researchers, scientists, engineers, and laboratory workers in the field of drug discovery and development, who want to learn about the latest techniques in machine learning and AI, as well as information technology professionals who are interested in the application of machine learning and artificial intelligence in drug development.

Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare

Author : Ghita Kouadri Mostefaoui,S. M. Riazul Islam,Faisal Tariq
Publisher : CRC Press
Page : 328 pages
File Size : 54,8 Mb
Release : 2023-03-30
Category : Computers
ISBN : 9781000823158

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Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare by Ghita Kouadri Mostefaoui,S. M. Riazul Islam,Faisal Tariq Pdf

Features In-depth coverage of the role of AI in smart healthcare. Research guideline for AI and data science researchers/practitioners interested in the healthcare sector. Comprehensive coverage on security and privacy issues for AI in smart healthcare.

Artificial Intelligence in Medical Imaging

Author : Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publisher : Springer
Page : 373 pages
File Size : 49,7 Mb
Release : 2019-01-29
Category : Medical
ISBN : 9783319948782

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Artificial Intelligence in Medical Imaging by Erik R. Ranschaert,Sergey Morozov,Paul R. Algra Pdf

This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Predictive Intelligence in Medicine

Author : Islem Rekik,Ehsan Adeli,Sang Hyun Park
Publisher : Springer Nature
Page : 191 pages
File Size : 48,7 Mb
Release : 2019-10-10
Category : Computers
ISBN : 9783030322816

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Predictive Intelligence in Medicine by Islem Rekik,Ehsan Adeli,Sang Hyun Park Pdf

This book constitutes the proceedings of the Second International Workshop on Predictive Intelligence in Medicine, PRIME 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 18 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine.

Mobile Technology for Adaptive Aging

Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Board on Behavioral, Cognitive, and Sensory Sciences
Publisher : National Academies Press
Page : 147 pages
File Size : 44,8 Mb
Release : 2020-10-25
Category : Social Science
ISBN : 9780309680868

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Mobile Technology for Adaptive Aging by National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Board on Behavioral, Cognitive, and Sensory Sciences Pdf

To explore how mobile technology can be employed to enhance the lives of older adults, the Board on Behavioral, Cognitive, and Sensory Sciences of the National Academies of Sciences, Engineering, and Medicine commissioned 6 papers, which were presented at a workshop held on December 11 and 12, 2019. These papers review research on mobile technologies and aging, and highlight promising avenues for further research.

Machine Learning Techniques on Gene Function Prediction Volume II

Author : Quan Zou,Arun Kumar Sangaiah,Dariusz Mrozek
Publisher : Frontiers Media SA
Page : 264 pages
File Size : 50,5 Mb
Release : 2023-04-11
Category : Science
ISBN : 9782889766321

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Machine Learning Techniques on Gene Function Prediction Volume II by Quan Zou,Arun Kumar Sangaiah,Dariusz Mrozek Pdf

Smart Healthcare Systems

Author : Adwitiya Sinha,Megha Rathi
Publisher : CRC Press
Page : 332 pages
File Size : 46,6 Mb
Release : 2019-07-24
Category : Computers
ISBN : 9780429670282

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Smart Healthcare Systems by Adwitiya Sinha,Megha Rathi Pdf

About the Book The book provides details of applying intelligent mining techniques for extracting and pre-processing medical data from various sources, for application-based healthcare research. Moreover, different datasets are used, thereby exploring real-world case studies related to medical informatics. This book would provide insight to the learners about Machine Learning, Data Analytics, and Sustainable Computing. Salient Features of the Book Exhaustive coverage of Data Analysis using R Real-life healthcare models for: Visually Impaired Disease Diagnosis and Treatment options Applications of Big Data and Deep Learning in Healthcare Drug Discovery Complete guide to learn the knowledge discovery process, build versatile real life healthcare applications Compare and analyze recent healthcare technologies and trends Target Audience This book is mainly targeted at researchers, undergraduate, postgraduate students, academicians, and scholars working in the area of data science and its application to health sciences. Also, the book is beneficial for engineers who are engaged in developing actual healthcare solutions.