Foundations Of Artificial Intelligence In Healthcare And Bioscience

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Foundations of Artificial Intelligence in Healthcare and Bioscience

Author : Louis J. Catania
Publisher : Academic Press
ISBN 13 : 0323860052
Total Pages : 562 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Foundations of Artificial Intelligence in Healthcare and Bioscience by : Louis J. Catania

Download or read book Foundations of Artificial Intelligence in Healthcare and Bioscience written by Louis J. Catania and published by Academic Press. This book was released on 2020-11-25 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundational Handbook of Artificial Intelligence in Healthcare and Bioscience: A User Friendly Guide for IT Professionals, Healthcare Providers, Researchers, and Clinicians uses color-coded illustrations to explain AI from its basics to modern technologies. Other sections cover extensive, current literature research and citations regarding AI’s role in the business and clinical aspects of health care. The book provides readers with a unique opportunity to appreciate AI technology in practical terms, understand its applications, and realize its profound influence on the clinical and business aspects of health care. Artificial Intelligence is a disruptive technology that is having a profound and growing influence on the business of health care as well as medical diagnosis, treatment, research and clinical delivery. The AI relationships in health care are complex, but understandable, especially when discussed and developed from their foundational elements through to their practical applications in health care. Provides an illustrated, foundational guide and comprehensive descriptions of what Artificial Intelligence is and how it functions Integrates a comprehensive discussion of AI applications in the business of health care Presents in-depth clinical and AI-related discussions on diagnostic medicine, therapeutic medicine, and prevalent disease categories with an emphasis on immunology and genetics, the two categories most influenced by AI Includes comprehensive coverage of a variety of AI treatment applications, including medical/pharmaceutical care, nursing care, stem cell therapies, robotics, and 10 common disease categories with AI applications

A Biologist’s Guide to Artificial Intelligence

Author : Ambreen Hamadani
Publisher : Elsevier
ISBN 13 : 0443240000
Total Pages : 370 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis A Biologist’s Guide to Artificial Intelligence by : Ambreen Hamadani

Download or read book A Biologist’s Guide to Artificial Intelligence written by Ambreen Hamadani and published by Elsevier. This book was released on 2024-03-15 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learning Equips with new data mining strategies an easy interface into the world of Artificial Intelligence Enables researchers to enhance their own sphere of researching Artificial Intelligence

Artificial Intelligence and Machine Learning in Health Care and Medical Sciences

Author : Gyorgy J. Simon
Publisher : Springer Nature
ISBN 13 : 3031393554
Total Pages : 824 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Artificial Intelligence and Machine Learning in Health Care and Medical Sciences by : Gyorgy J. Simon

Download or read book Artificial Intelligence and Machine Learning in Health Care and Medical Sciences written by Gyorgy J. Simon and published by Springer Nature. This book was released on with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence in Healthcare Industry

Author : Jyotismita Talukdar
Publisher : Springer
ISBN 13 : 9789819931569
Total Pages : 0 pages
Book Rating : 4.9/5 (315 download)

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Book Synopsis Artificial Intelligence in Healthcare Industry by : Jyotismita Talukdar

Download or read book Artificial Intelligence in Healthcare Industry written by Jyotismita Talukdar and published by Springer. This book was released on 2023-10-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic evolution of artificial intelligence (AI), its applications, challenges and solutions in the field of healthcare. The book mainly covers the foundations and various methods of learning in artificial intelligence with its application in healthcare industry. This book provides a comprehensive introduction to data analysis using AI as a tool in the generation, normalization and analysis of healthcare data in association with several evaluation techniques and accuracy measurements. The book is divided into three major sections describing the basic foundations of AI and its associated algorithms, history of artificial intelligence in healthcare, recent developments and several modeling techniques for the same. The last section of the book provides insights into several implementations and methods of evaluation and accuracy prediction for healthcare analysis in AI. Extensive use of data for analysis and prediction using several technologies has transformed the lives of normal people indirectly effecting our process to communicate, learn, work and socialize within the society. Thus, the book also provides an insight into the ethics of AI that is very vital in the process of implementation and evaluation of healthcare data. The book provides an organized analysis to a considerable part of data in a digitized society. In view of this, it covers the theory, methodology, perfection and verification of empirical work for health-related data processing. Particular attention is devoted to in-depth experiments and applications.

Artificial Intelligence in the Field of Health

Author : Dr. Shahul Hameed Pakkir Mohamed
Publisher : Priya Lokare
ISBN 13 : 8195694152
Total Pages : 161 pages
Book Rating : 4.1/5 (956 download)

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Book Synopsis Artificial Intelligence in the Field of Health by : Dr. Shahul Hameed Pakkir Mohamed

Download or read book Artificial Intelligence in the Field of Health written by Dr. Shahul Hameed Pakkir Mohamed and published by Priya Lokare. This book was released on 2022-07-08 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) and related propels are logically dominating in business and society, and are beginning to be applied to clinical benefits. These advancements might perhaps change various pieces of patient thought, as well as administrative cycles inside the provider, payer, and medication affiliations. There are currently different investigation studies recommending that AI can continue as well as or better than individuals at key clinical benefits tasks, such as diagnosing disease. Today, estimations are at this point beating radiologists at spotting perilous developments and guiding experts in how to fabricate associates for costly clinical starters. In any case, in light of multiple factors, we acknowledge that it will be various earlier years AI replaces individuals for far-reaching clinical cycle regions. In this article, we depict both the potential that AI offers to robotize parts of care and a piece of the blocks too fast execution of AI in clinical benefits.

Foundations of Biomedical Knowledge Representation

Author : Arjen Hommersom
Publisher : Springer
ISBN 13 : 3319280074
Total Pages : 339 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Foundations of Biomedical Knowledge Representation by : Arjen Hommersom

Download or read book Foundations of Biomedical Knowledge Representation written by Arjen Hommersom and published by Springer. This book was released on 2016-01-07 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medicine and health care are currently faced with a significant rise in their complexity. This is partly due to the progress made during the past three decades in the fundamental biological understanding of the causes of health and disease at the molecular, (sub)cellular, and organ level. Since the end of the 1970s, when knowledge representation and reasoning in the biomedical field became a separate area of research, huge progress has been made in the development of methods and tools that are finally able to impact on the way medicine is being practiced. Even though there are huge differences in the techniques and methods used by biomedical researchers, there is now an increasing tendency to share research results in terms of formal knowledge representation methods, such as ontologies, statistical models, network models, and mathematical models. As there is an urgent need for health-care professionals to make better decisions, computer-based support using this knowledge is now becoming increasingly important. It may also be the only way to integrate research results from the different parts of the spectrum of biomedical and clinical research. The aim of this book is to shed light on developments in knowledge representation at different levels of biomedical application, ranging from human biology to clinical guidelines, and using different techniques, from probability theory and differential equations to logic. The book starts with two introductory chapters followed by 18 contributions organized in the following topical sections: diagnosis of disease; monitoring of health and disease and conformance; assessment of health and personalization; prediction and prognosis of health and disease; treatment of disease; and recommendations.

A Biologist's Guide to Artificial Intelligence

Author : Ambreen Hamadani
Publisher : Elsevier
ISBN 13 : 0443240019
Total Pages : 368 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis A Biologist's Guide to Artificial Intelligence by : Ambreen Hamadani

Download or read book A Biologist's Guide to Artificial Intelligence written by Ambreen Hamadani and published by Elsevier. This book was released on 2024-03 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Biologist's Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist's perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms.

Artificial Intelligence and Machine Learning-Powered Smart Finance

Author : Taneja, Sanjay
Publisher : IGI Global
ISBN 13 :
Total Pages : 378 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Artificial Intelligence and Machine Learning-Powered Smart Finance by : Taneja, Sanjay

Download or read book Artificial Intelligence and Machine Learning-Powered Smart Finance written by Taneja, Sanjay and published by IGI Global. This book was released on 2024-02-12 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the field of finance, the pervasive influence of algorithms has transformed the very fabric of the industry. Today, over 75% of trades are orchestrated by algorithms, making them the linchpin for trade automation, predictions, and decision-making. This algorithmic reliance, while propelling financial services into unprecedented efficiency, has also ushered in a host of challenges. As the financial sector becomes increasingly algorithm-driven, concerns about risk assessment, market manipulation, and the ethical implications of automated decision-making have taken center stage. Artificial Intelligence and Machine Learning-Powered Smart Finance, meticulously examines the intersection of computational finance and advanced algorithms and the challenges associated with this technology. As algorithms permeate various facets of financial services, the book takes a deep dive into their applications, spanning forecasting, portfolio optimization, market trends analysis, and cryptoanalysis. It sheds light on the role of AI-based algorithms in personnel selection, implementing trusted financial services, developing recommendation systems for financial platforms, and detecting fraud, presenting a compelling case for the integration of innovative solutions in the financial sector. As the book unravels the intricate tapestry of algorithmic applications in finance, it also illuminates the ethical considerations and governance frameworks essential for navigating the delicate balance between technological innovation and responsible financial practices.

Impact of Digital Transformation on the Development of New Business Models and Consumer Experience

Author : Rodrigues, Maria Antónia
Publisher : IGI Global
ISBN 13 : 179989181X
Total Pages : 347 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Impact of Digital Transformation on the Development of New Business Models and Consumer Experience by : Rodrigues, Maria Antónia

Download or read book Impact of Digital Transformation on the Development of New Business Models and Consumer Experience written by Rodrigues, Maria Antónia and published by IGI Global. This book was released on 2022-03-11 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a highly competitive market, digital transformation with internet of things, artificial intelligence, and other innovative technological trends are elements of differentiations and are important milestones in business development and consumer interaction, particularly in services. As a result, there are several new business models anchored in these digital and technological environments and new experiences provided to services consumers and firms that need to be examined. Impact of Digital Transformation on the Development of New Business Models and Consumer Experience provides relevant theoretical and empirical research findings and innovative and multifaceted perspectives on how digital transformation and other innovative technologies can drive new business models and create valued experiences for consumers and firms. Covering topics such as business models, consumer behavior, and gamification, this publication is ideal for industry professionals, managers, business owners, practitioners, researchers, professors, academicians, and students.

Intelligent Systems in Medicine and Health

Author : Trevor A. Cohen
Publisher : Springer Nature
ISBN 13 : 3031091086
Total Pages : 607 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Intelligent Systems in Medicine and Health by : Trevor A. Cohen

Download or read book Intelligent Systems in Medicine and Health written by Trevor A. Cohen and published by Springer Nature. This book was released on 2022-11-09 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook comprehensively covers the latest state-of-the-art methods and applications of artificial intelligence (AI) in medicine, placing these developments into a historical context. Factors that assist or hinder a particular technique to improve patient care from a cognitive informatics perspective are identified and relevant methods and clinical applications in areas including translational bioinformatics and precision medicine are discussed. This approach enables the reader to attain an accurate understanding of the strengths and limitations of these emerging technologies and how they relate to the approaches and systems that preceded them. With topics covered including knowledge-based systems, clinical cognition, machine learning and natural language processing, Intelligent Systems in Medicine and Health: The Role of AI details a range of the latest AI tools and technologies within medicine. Suggested additional readings and review questions reinforce the key points covered and ensure readers can further develop their knowledge. This makes it an indispensable resource for all those seeking up-to-date information on the topic of AI in medicine, and one that provides a sound basis for the development of graduate and undergraduate course materials.

Artificial Intelligence in Healthcare and Medicine

Author : Kayvan Najarian
Publisher : CRC Press
ISBN 13 : 1000565815
Total Pages : 300 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Artificial Intelligence in Healthcare and Medicine by : Kayvan Najarian

Download or read book Artificial Intelligence in Healthcare and Medicine written by Kayvan Najarian and published by CRC Press. This book was released on 2022-04-06 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.

Machine Intelligence for Healthcare

Author : Francis X. Campion
Publisher :
ISBN 13 : 9781542924948
Total Pages : 346 pages
Book Rating : 4.9/5 (249 download)

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Book Synopsis Machine Intelligence for Healthcare by : Francis X. Campion

Download or read book Machine Intelligence for Healthcare written by Francis X. Campion and published by . This book was released on 2017-02-02 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Intelligence for Healthcare is a must read for physician leaders, health insurance executives, clinical researchers, public health officials, data scientists and software engineers seeking to understand this pivotal innovation in the information revolution in healthcare. MI for Healthcare provides a detailed introduction of Machine Intelligence, then takes the reader on a journey through the basics of machine learning, topological data analysis and applications of machine intelligence software for healthcare and life sciences. Over 20 case studies cover topics related to clinical variation analysis, hospital clinical pathways, population health management, genetic analysis, precision medicine, healthcare revenue cycle, and payment integrity. The book includes a detailed introduction of the mathematics of topology and concepts of machine learning algorithms. This provides an understanding for the central role which machine intelligence software is now playing in the emergence of the "learning healthcare system" and success in the new world of value-based healthcare delivery.

IoT and Analytics in Renewable Energy Systems (Volume 1)

Author : O.V. Gnana Swathika
Publisher : CRC Press
ISBN 13 : 1000909794
Total Pages : 471 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis IoT and Analytics in Renewable Energy Systems (Volume 1) by : O.V. Gnana Swathika

Download or read book IoT and Analytics in Renewable Energy Systems (Volume 1) written by O.V. Gnana Swathika and published by CRC Press. This book was released on 2023-08-11 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Smart grid technologies include sensing and measurement technologies, advanced components aided with communications and control methods along with improved interfaces and decision support systems. Smart grid techniques support the extensive inclusion of clean renewable generation in power systems. Smart grid use also promotes energy saving in power systems. Cyber security objectives for the smart grid are availability, integrity and confidentiality. Five salient features of this book are as follows: AI and IoT in improving resilience of smart energy infrastructure IoT, smart grids and renewable energy: an economic approach AI and ML towards sustainable solar energy Electrical vehicles and smart grid Intelligent condition monitoring for solar and wind energy systems

Fundamentals of Machine Learning and Deep Learning in Medicine

Author : Reza Borhani
Publisher : Springer Nature
ISBN 13 : 3031195027
Total Pages : 201 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Fundamentals of Machine Learning and Deep Learning in Medicine by : Reza Borhani

Download or read book Fundamentals of Machine Learning and Deep Learning in Medicine written by Reza Borhani and published by Springer Nature. This book was released on 2022-11-18 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an accessible introduction to the foundations of machine learning and deep learning in medicine for medical students, researchers, and professionals who are not necessarily initiated in advanced mathematics but yearn for a better understanding of this disruptive technology and its impact on medicine. Once an esoteric subject known to few outside of computer science and engineering departments, today artificial intelligence (AI) is a widely popular technology used by scholars from all across the academic universe. In particular, recent years have seen a great deal of interest in the AI subfields of machine learning and deep learning from researchers in medicine and life sciences, evidenced by the rapid growth in the number of articles published on the topic in peer-reviewed medical journals over the last decade. The demand for high-quality educational resources in this area has never been greater than it is today, and will only continue to grow at a rapid pace. Expert authors remove the veil of unnecessary complexity that often surrounds machine learning and deep learning by employing a narrative style that emphasizes intuition in place of abstract mathematical formalisms, allowing them to strike a delicate balance between practicality and theoretical rigor in service of facilitating the reader’s learning experience. Topics covered in the book include: mathematical encoding of medical data, linear regression and classification, nonlinear feature engineering, deep learning, convolutional and recurrent neural networks, and reinforcement learning. Each chapter ends with a collection of exercises for readers to practice and test their knowledge. This is an ideal introduction for medical students, professionals, and researchers interested in learning more about machine learning and deep learning. Readers who have taken at least one introductory mathematics course at the undergraduate-level (e.g., biostatistics or calculus) will be well-equipped to use this book without needing any additional prerequisites.

Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare

Author : Ilker Ozsahin
Publisher : Bentham Science Publishers
ISBN 13 : 168108872X
Total Pages : 316 pages
Book Rating : 4.6/5 (81 download)

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Book Synopsis Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare by : Ilker Ozsahin

Download or read book Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare written by Ilker Ozsahin and published by Bentham Science Publishers. This book was released on 2021-11-18 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an ideal foundation for readers to understand the application of artificial intelligence (AI) and machine learning (ML) techniques to expert systems in the healthcare sector. It starts with an introduction to the topic and presents chapters which progressively explain decision-making theory that helps solve problems which have multiple criteria that can affect the outcome of a decision. Key aspects of the subject such as machine learning in healthcare, prediction techniques, mathematical models and classification of healthcare problems are included along with chapters which delve in to advanced topics on data science (deep-learning, artificial neural networks, etc.) and practical examples (influenza epidemiology and retinoblastoma treatment analysis). Key Features: - Introduces readers to the basics of AI and ML in expert systems for healthcare - Focuses on a problem solving approach to the topic - Provides information on relevant decision-making theory and data science used in the healthcare industry - Includes practical applications of AI and ML for advanced readers - Includes bibliographic references for further reading The reference is an accessible source of knowledge on multi-criteria decision-support systems in healthcare for medical consultants, healthcare policy makers, researchers in the field of medical biotechnology, oncology and pharmaceutical research and development.

Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization

Author : Singh, Amandeep
Publisher : IGI Global
ISBN 13 :
Total Pages : 285 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization by : Singh, Amandeep

Download or read book Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization written by Singh, Amandeep and published by IGI Global. This book was released on 2023-12-29 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, algorithms steer and inform more than 75% of modern trades. These mathematical constructs play an intricate role in automating processes, predicting market trends, optimizing portfolios, and fortifying decision-making in the financial domain. In an era where algorithms underpin the very foundation of financial services, it is imperative to hold a deep understanding of the intricate web of computational finance. Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization takes a comprehensive approach, spotlighting the fusion of artificial intelligence(AI) and algorithms in financial operations. The chapters explore the expansive landscape of algorithmic applications, from scrutinizing market trends to managing risks. The emphasis extends to AI-driven personnel selection, implementing trusted financial services, crafting recommendation systems for financial platforms, and critical fraud detection. This book serves as a vital resource for researchers, students, and practitioners. Its core strength lies in discussing AI-based algorithms as a catalyst for evolving market trends. It provides algorithmic solutions for stock markets, portfolio optimization, and robust financial fraud detection mechanisms.

Artificial Intelligence in Medicine

Author : Lei Xing
Publisher : Academic Press
ISBN 13 : 0128212586
Total Pages : 570 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Artificial Intelligence in Medicine by : Lei Xing

Download or read book Artificial Intelligence in Medicine written by Lei Xing and published by Academic Press. This book was released on 2020-09-03 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach