Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
Total Pages: 385
Release: 2020-06-21
Genre: Computers
ISBN: 0128184396

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, Machine Learning, and Optimization Tools for Smart Cities

Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities
Author: Panos M. Pardalos
Publisher: Springer Nature
Total Pages: 239
Release: 2022-01-09
Genre: Mathematics
ISBN: 3030844595

This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which contribute to the optimization of urban features towards forming smart, sustainable, and livable future cities. Special features include: New research on the design of city elements and smart systems with respect to new technologies and scientific thinking Discussions on the theoretical background that lead to smart cities for the future New technologies and principles of research that can promote ideas of artificial intelligence and machine learning in optimized urban environments The book engages students and researchers in the subjects of artificial intelligence, machine learning, and optimization tools in smart sustainable cities as eminent international experts contribute their research results and thinking in its chapters. Overall, its audience can benefit from a variety of disciplines including, architecture, engineering, physics, mathematics, computer science, and related fields.

Artificial Intelligence in Tissue and Organ Regeneration

Artificial Intelligence in Tissue and Organ Regeneration
Author: Chandra P. Sharma
Publisher: Elsevier
Total Pages: 344
Release: 2023-08-18
Genre: Science
ISBN: 0443184992

Artificial Intelligence in Tissue and Organ Regeneration discusses the role of artificial intelligence as a highly sought-after technology in the area of organ and tissue regeneration. Certain groups have made significant progress in mass producing mini organs and organoids from stem cells utilizing such techniques. As time goes on, there will be a need to improve these procedures, protocols, regulatory guidelines, and their clinical implications. - Integrates existing literature in a highly interdisciplinary area - Presents comprehensive current and future perspectives, combining artificial intelligence and machine learning with organ and tissue regeneration - Provides new and emerging technology that is useful in healthcare and the medical field

Responsible Artificial Intelligence Re-engineering the Global Public Health Ecosystem

Responsible Artificial Intelligence Re-engineering the Global Public Health Ecosystem
Author: Dominique J Monlezun
Publisher: Elsevier
Total Pages: 277
Release: 2024-06-07
Genre: Computers
ISBN: 0443215960

Artificial intelligence Re-Engineering the Global Public Health Ecosystem: A Humanity Worth Saving provides a unifying strategic vision (and principles and examples operationalizing it) for the AI-accelerated effective, efficient, and equitable global public health of the future. Readers will find an ecosystem-based approach to understanding how AI is transforming and globalizing public health (and thus our underlying political economics, contextualized in our diverse cultures). The book integrates data architecture, digital health ecosystem, algorithms (including machine and deep learning and artificial general intelligence), quantum computing, global disease surveillance, adaptive value supply chains, demographic shifts, integral development, network science, health financing, healthcare system design, and multicultural global ethics underlying diverse political economic systems in a clear and concrete way forward together, within a divided but digitized and globalized world. Written by the world's first triple doctorate-trained physician-data scientist and AI ethicist, this book is a compelling and coherent guide to help empower and equip AI developers, students, practitioners, policymakers, researchers, and leaders in digital technology, public health, healthcare, health policy, public policy, political science, economics, and ethics to generate the healthcare solutions that will define humanity's next era. - Details the first comprehensive ecosystem analysis of global public health revolutionized by AI. - Uses concrete examples to explain the dominant players and trends determining health's future, including through data architecture, financing, political economics, demographics, security, and multicultural ethics. - Provides a successful full-spectrum formula for governments, institutions, companies, and communities to scale equitable health globally while respecting local identities and values.

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems
Author: Alexandre Dolgui
Publisher: Springer Nature
Total Pages: 779
Release: 2021-08-31
Genre: Computers
ISBN: 303085874X

The five-volume set IFIP AICT 630, 631, 632, 633, and 634 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2021, held in Nantes, France, in September 2021.* The 378 papers presented were carefully reviewed and selected from 529 submissions. They discuss artificial intelligence techniques, decision aid and new and renewed paradigms for sustainable and resilient production systems at four-wall factory and value chain levels. The papers are organized in the following topical sections: Part I: artificial intelligence based optimization techniques for demand-driven manufacturing; hybrid approaches for production planning and scheduling; intelligent systems for manufacturing planning and control in the industry 4.0; learning and robust decision support systems for agile manufacturing environments; low-code and model-driven engineering for production system; meta-heuristics and optimization techniques for energy-oriented manufacturing systems; metaheuristics for production systems; modern analytics and new AI-based smart techniques for replenishment and production planning under uncertainty; system identification for manufacturing control applications; and the future of lean thinking and practice Part II: digital transformation of SME manufacturers: the crucial role of standard; digital transformations towards supply chain resiliency; engineering of smart-product-service-systems of the future; lean and Six Sigma in services healthcare; new trends and challenges in reconfigurable, flexible or agile production system; production management in food supply chains; and sustainability in production planning and lot-sizing Part III: autonomous robots in delivery logistics; digital transformation approaches in production management; finance-driven supply chain; gastronomic service system design; modern scheduling and applications in industry 4.0; recent advances in sustainable manufacturing; regular session: green production and circularity concepts; regular session: improvement models and methods for green and innovative systems; regular session: supply chain and routing management; regular session: robotics and human aspects; regular session: classification and data management methods; smart supply chain and production in society 5.0 era; and supply chain risk management under coronavirus Part IV: AI for resilience in global supply chain networks in the context of pandemic disruptions; blockchain in the operations and supply chain management; data-based services as key enablers for smart products, manufacturing and assembly; data-driven methods for supply chain optimization; digital twins based on systems engineering and semantic modeling; digital twins in companies first developments and future challenges; human-centered artificial intelligence in smart manufacturing for the operator 4.0; operations management in engineer-to-order manufacturing; product and asset life cycle management for smart and sustainable manufacturing systems; robotics technologies for control, smart manufacturing and logistics; serious games analytics: improving games and learning support; smart and sustainable production and supply chains; smart methods and techniques for sustainable supply chain management; the new digital lean manufacturing paradigm; and the role of emerging technologies in disaster relief operations: lessons from COVID-19 Part V: data-driven platforms and applications in production and logistics: digital twins and AI for sustainability; regular session: new approaches for routing problem solving; regular session: improvement of design and operation of manufacturing systems; regular session: crossdock and transportation issues; regular session: maintenance improvement and lifecycle management; regular session: additive manufacturing and mass customization; regular session: frameworks and conceptual modelling for systems and services efficiency; regular session: optimization of production and transportation systems; regular session: optimization of supply chain agility and reconfigurability; regular session: advanced modelling approaches; regular session: simulation and optimization of systems performances; regular session: AI-based approaches for quality and performance improvement of production systems; and regular session: risk and performance management of supply chains *The conference was held online.

The Cambridge Handbook of Responsible Artificial Intelligence

The Cambridge Handbook of Responsible Artificial Intelligence
Author: Silja Voeneky
Publisher: Cambridge University Press
Total Pages: 1440
Release: 2022-11-17
Genre: Law
ISBN: 1009207881

In the past decade, artificial intelligence (AI) has become a disruptive force around the world, offering enormous potential for innovation but also creating hazards and risks for individuals and the societies in which they live. This volume addresses the most pressing philosophical, ethical, legal, and societal challenges posed by AI. Contributors from different disciplines and sectors explore the foundational and normative aspects of responsible AI and provide a basis for a transdisciplinary approach to responsible AI. This work, which is designed to foster future discussions to develop proportional approaches to AI governance, will enable scholars, scientists, and other actors to identify normative frameworks for AI to allow societies, states, and the international community to unlock the potential for responsible innovation in this critical field. This book is also available as Open Access on Cambridge Core.

Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing

Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing
Author: Amit Kumar Tyagi
Publisher: CRC Press
Total Pages: 419
Release: 2024-10-23
Genre: Computers
ISBN: 1040151396

Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.