Machine Learning and AI for Healthcare

Big Data for Improved Health Outcomes

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Author: Arjun Panesar

Publisher: Apress

ISBN: 1484237994

Category: Computers

Page: 368

View: 9322

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll Learn Gain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agents Who This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.

Machine Learning for Healthcare Analytics Projects

Build smart AI applications using neural network methodologies across the healthcare vertical market

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Author: Eduonix Learning Solutions

Publisher: Packt Publishing Ltd

ISBN: 1789532523

Category: Computers

Page: 134

View: 6006

Create real-world machine learning solutions using NumPy, pandas, matplotlib, and scikit-learn Key Features Develop a range of healthcare analytics projects using real-world datasets Implement key machine learning algorithms using a range of libraries from the Python ecosystem Accomplish intermediate-to-complex tasks by building smart AI applications using neural network methodologies Book Description Machine Learning (ML) has changed the way organizations and individuals use data to improve the efficiency of a system. ML algorithms allow strategists to deal with a variety of structured, unstructured, and semi-structured data. Machine Learning for Healthcare Analytics Projects is packed with new approaches and methodologies for creating powerful solutions for healthcare analytics. This book will teach you how to implement key machine learning algorithms and walk you through their use cases by employing a range of libraries from the Python ecosystem. You will build five end-to-end projects to evaluate the efficiency of Artificial Intelligence (AI) applications for carrying out simple-to-complex healthcare analytics tasks. With each project, you will gain new insights, which will then help you handle healthcare data efficiently. As you make your way through the book, you will use ML to detect cancer in a set of patients using support vector machines (SVMs) and k-Nearest neighbors (KNN) models. In the final chapters, you will create a deep neural network in Keras to predict the onset of diabetes in a huge dataset of patients. You will also learn how to predict heart diseases using neural networks. By the end of this book, you will have learned how to address long-standing challenges, provide specialized solutions for how to deal with them, and carry out a range of cognitive tasks in the healthcare domain. What you will learn Explore super imaging and natural language processing (NLP) to classify DNA sequencing Detect cancer based on the cell information provided to the SVM Apply supervised learning techniques to diagnose autism spectrum disorder (ASD) Implement a deep learning grid and deep neural networks for detecting diabetes Analyze data from blood pressure, heart rate, and cholesterol level tests using neural networks Use ML algorithms to detect autistic disorders Who this book is for Machine Learning for Healthcare Analytics Projects is for data scientists, machine learning engineers, and healthcare professionals who want to implement machine learning algorithms to build smart AI applications. Basic knowledge of Python or any programming language is expected to get the most from this book.

Demystifying Big Data and Machine Learning for Healthcare

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Author: Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz

Publisher: CRC Press

ISBN: 1315389312

Category: Medical

Page: 210

View: 5710

Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Machine Learning for Health Informatics

State-of-the-Art and Future Challenges

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Author: Andreas Holzinger

Publisher: Springer

ISBN: 3319504789

Category: Computers

Page: 481

View: 2851

Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.

Ikioo® 21st Century Medicine

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Author: Ayman Salem

Publisher: Ayman Salem

ISBN: 9780997509618

Category:

Page: N.A

View: 4755

ikioo(R) 21st Century Medicine: Artificial Intelligence for Health Professionals

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

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Author: Ashok N. Srivastava,Jiawei Han

Publisher: CRC Press

ISBN: 1439841799

Category: Computers

Page: 502

View: 7687

Machine Learning and Knowledge Discovery for Engineering Systems Health Management presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. With contributions from many top authorities on the subject, this volume is the first to bring together the two areas of machine learning and systems health management. Divided into three parts, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management. The first part of the text describes data-driven methods for anomaly detection, diagnosis, and prognosis of massive data streams and associated performance metrics. It also illustrates the analysis of text reports using novel machine learning approaches that help detect and discriminate between failure modes. The second part focuses on physics-based methods for diagnostics and prognostics, exploring how these methods adapt to observed data. It covers physics-based, data-driven, and hybrid approaches to studying damage propagation and prognostics in composite materials and solid rocket motors. The third part discusses the use of machine learning and physics-based approaches in distributed data centers, aircraft engines, and embedded real-time software systems. Reflecting the interdisciplinary nature of the field, this book shows how various machine learning and knowledge discovery techniques are used in the analysis of complex engineering systems. It emphasizes the importance of these techniques in managing the intricate interactions within and between the systems to maintain a high degree of reliability.

Leben 3.0

Mensch sein im Zeitalter Künstlicher Intelligenz

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Author: Max Tegmark

Publisher: Ullstein Buchverlage

ISBN: 3843716706

Category: Social Science

Page: 528

View: 2844

Die Nobelpreis-Schmiede Massachusetts Institute of Technology ist der bedeutendste technologische Think Tank der USA. Dort arbeitet Professor Max Tegmark mit den weltweit führenden Entwicklern künstlicher Intelligenz zusammen, die ihm exklusive Einblicke in ihre Labors gewähren. Die Erkenntnisse, die er daraus zieht, sind atemberaubend und zutiefst verstörend zugleich. Neigt sich die Ära der Menschen dem Ende zu? Der Physikprofessor Max Tegmark zeigt anhand der neusten Forschung, was die Menschheit erwartet. Hier eine Auswahl möglicher Szenarien: - Eroberer: Künstliche Intelligenz übernimmt die Macht und entledigt sich der Menschheit mit Methoden, die wir noch nicht einmal verstehen. - Der versklavte Gott: Die Menschen bemächtigen sich einer superintelligenten künstlichen Intelligenz und nutzen sie, um Hochtechnologien herzustellen. - Umkehr: Der technologische Fortschritt wird radikal unterbunden und wir kehren zu einer prä-technologischen Gesellschaft im Stil der Amish zurück. - Selbstzerstörung: Superintelligenz wird nicht erreicht, weil sich die Menschheit vorher nuklear oder anders selbst vernichtet. - Egalitäres Utopia: Es gibt weder Superintelligenz noch Besitz, Menschen und kybernetische Organismen existieren friedlich nebeneinander. Max Tegmark bietet kluge und fundierte Zukunftsszenarien basierend auf seinen exklusiven Einblicken in die aktuelle Forschung zur künstlichen Intelligenz.

Machine Learning for Decision Makers

Cognitive Computing Fundamentals for Better Decision Making

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Author: Patanjali Kashyap

Publisher: Apress

ISBN: 1484229886

Category: Computers

Page: 355

View: 6673

Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.

Homo Deus

Eine Geschichte von Morgen

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Author: Yuval Noah Harari

Publisher: C.H.Beck

ISBN: 3406704026

Category: Social Science

Page: 576

View: 7705

In seinem Kultbuch „Eine kurze Geschichte der Menschheit“ erklärte Yuval Noah Harari, wie unsere Spezies die Erde erobern konnte. In „Homo Deus“ stößt er vor in eine noch verborgene Welt: die Zukunft. Was wird mit uns und unserem Planeten passieren, wenn die neuen Technologien dem Menschen gottgleiche Fähigkeiten verleihen – schöpferische wie zerstörerische – und das Leben selbst auf eine völlig neue Stufe der Evolution heben? Wie wird es dem Homo Sapiens ergehen, wenn er einen technikverstärkten Homo Deus erschafft, der sich vom heutigen Menschen deutlicher unterscheidet als dieser vom Neandertaler? Was bleibt von uns und der modernen Religion des Humanismus, wenn wir Maschinen konstruieren, die alles besser können als wir? In unserer Gier nach Gesundheit, Glück und Macht könnten wir uns ganz allmählich so weit verändern, bis wir schließlich keine Menschen mehr sind.

Artificial Intelligence and Social Work

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Author: Milind Tambe,Eric Rice

Publisher: Cambridge University Press

ISBN: 1108425992

Category: Computers

Page: 280

View: 6342

An introductory guide with real-life examples on using AI to help homeless youth, diabetes patients, and other social welfare interventions.

Künstliche Intelligenz

ein moderner Ansatz

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Author: Stuart J. Russell,Stuart Russell,Peter Norvig

Publisher: N.A

ISBN: 9783827370891

Category:

Page: 1327

View: 8746

Medical Applications of Artificial Intelligence

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Author: Arvin Agah

Publisher: CRC Press

ISBN: 143988434X

Category: Medical

Page: 526

View: 1072

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Applications of Artificial Intelligence reviews the research, focusing on state-of-the-art projects in the field. The book captures the breadth and depth of the medical applications of artificial intelligence, exploring new developments and persistent challenges.

Machine Learning Applications Using Python

Cases Studies from Healthcare, Retail, and Finance

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Author: Puneet Mathur

Publisher: Apress

ISBN: 1484237870

Category: Computers

Page: 379

View: 9462

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you’ll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You’ll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. What You Will Learn Discover applied machine learning processes and principles Implement machine learning in areas of healthcare, finance, and retail Avoid the pitfalls of implementing applied machine learning Build Python machine learning examples in the three subject areas Who This Book Is For Data scientists and machine learning professionals.

Artificial Intelligence for Games

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Author: Ian Millington,John Funge

Publisher: CRC Press

ISBN: 0123747317

Category: Art

Page: 872

View: 7151

Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's associated web site contains a library of C++ source code and demonstration programs, and a complete commercial source code library of AI algorithms and techniques. "Artificial Intelligence for Games - 2nd edition" will be highly useful to academics teaching courses on game AI, in that it includes exercises with each chapter. It will also include new and expanded coverage of the following: AI-oriented gameplay; Behavior driven AI; Casual games (puzzle games).

Machine Learning in Healthcare Informatics

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Author: Sumeet Dua,U. Rajendra Acharya,Prerna Dua

Publisher: Springer Science & Business Media

ISBN: 3642400175

Category: Computers

Page: 332

View: 1727

The book is a unique effort to represent a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. The book provides a unique compendium of current and emerging machine learning paradigms for healthcare informatics and reflects the diversity, complexity and the depth and breath of this multi-disciplinary area. The integrated, panoramic view of data and machine learning techniques can provide an opportunity for novel clinical insights and discoveries.

Artificial Intelligence XXXIV

37th SGAI International Conference on Artificial Intelligence, AI 2017, Cambridge, UK, December 12-14, 2017, Proceedings

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Author: Max Bramer,Miltos Petridis

Publisher: Springer

ISBN: 3319710788

Category: Computers

Page: 430

View: 5645

This book constitutes the proceedings of the 37th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, AI 2017, held in Cambridge, UK, in December 2017. The 25 full papers and 12 short papers presented in this volume were carefully reviewed and selected from 55 submissions. There are technical and application papers which were organized in topical sections named: machine learning and neural networks; machine learning, speech and vision and fuzzy logic; short technical papers; AI for healthcare; applications of machine learning; applications of neural networks and fuzzy logic; case-based reasoning; AI techniques; and short applications papers.

Knowledge Representation for Health Care

6th International Workshop, KR4HC 2014, held as part of the Vienna Summer of Logic, VSL 2014, Vienna, Austria, July 21, 2014. Revised Selected Papers

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Author: Silvia Miksch,David Riaño,Annette ten Teije

Publisher: Springer

ISBN: 3319132814

Category: Computers

Page: 175

View: 5854

This book constitutes the refereed proceedings of the 6th International Workshop on Knowledge Representation for Health Care, KR4HC 2014, held as part of the Vienna Summer of Logic, VSL 2014, in Vienna, Austria, in July 2014. The workshop aimed at attracting the interest of novel research and advances contributing in the definition, representation and exploitation of health care knowledge in medical informatics. The 12 revised full research papers and 4 short papers presented in this book were carefully reviewed and selected from 26 submissions.

Wireless Sensor Networks for Healthcare Applications

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Author: Terrance J. Dishongh,Michael McGrath

Publisher: Artech House

ISBN: 1596933062

Category: Medical care

Page: 246

View: 2321

This unique reference focuses on methods of application, validation and testing based on real deployments of sensor networks in the clinical and home environments. Key topics include healthcare and wireless sensors, sensor network applications, designs of experiments using sensors, data collection and decision making, clinical deployment of wireless sensor networks, contextual awareness medication prompting field trials in homes, social health monitoring, and the future of wireless sensor networks in healthcare.