Machine Learning In Chemical Safety And Health

Author : Qingsheng Wang
Publisher : John Wiley & Sons
ISBN 13 : 1119817501
Total Pages : 324 pages
Book Rating : 4.05/5 ( download)

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Download or read book Machine Learning in Chemical Safety and Health written by Qingsheng Wang and published by John Wiley & Sons. This book was released on 2022-10-21 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces Machine Learning Techniques and Tools and Provides Guidance on How to Implement Machine Learning Into Chemical Safety and Health-related Model Development There is a growing interest in the application of machine learning algorithms in chemical safety and health-related model development, with applications in areas including property and toxicity prediction, consequence prediction, and fault detection. This book is the first to review the current status of machine learning implementation in chemical safety and health research and to provide guidance for implementing machine learning techniques and algorithms into chemical safety and health research. Written by an international team of authors and edited by renowned experts in the areas of process safety and occupational and environmental health, sample topics covered within the work include: An introduction to the fundamentals of machine learning, including regression, classification and cross-validation, and an overview of software and tools Detailed reviews of various applications in the areas of chemical safety and health, including flammability prediction, consequence prediction, asset integrity management, predictive nanotoxicity and environmental exposure assessment, and more Perspective on the possible future development of this field Machine Learning in Chemical Safety and Health serves as an essential guide on both the fundamentals and applications of machine learning for industry professionals and researchers in the fields of process safety, chemical safety, occupational and environmental health, and industrial hygiene.

Author : Qingsheng Wang
Publisher : John Wiley & Sons
ISBN 13 : 111981748X
Total Pages : 324 pages
Book Rating : 4.82/5 ( download)

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Download or read book Machine Learning in Chemical Safety and Health written by Qingsheng Wang and published by John Wiley & Sons. This book was released on 2023-02-06 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces Machine Learning Techniques and Tools and Provides Guidance on How to Implement Machine Learning Into Chemical Safety and Health-related Model Development There is a growing interest in the application of machine learning algorithms in chemical safety and health-related model development, with applications in areas including property and toxicity prediction, consequence prediction, and fault detection. This book is the first to review the current status of machine learning implementation in chemical safety and health research and to provide guidance for implementing machine learning techniques and algorithms into chemical safety and health research. Written by an international team of authors and edited by renowned experts in the areas of process safety and occupational and environmental health, sample topics covered within the work include: An introduction to the fundamentals of machine learning, including regression, classification and cross-validation, and an overview of software and tools Detailed reviews of various applications in the areas of chemical safety and health, including flammability prediction, consequence prediction, asset integrity management, predictive nanotoxicity and environmental exposure assessment, and more Perspective on the possible future development of this field Machine Learning in Chemical Safety and Health serves as an essential guide on both the fundamentals and applications of machine learning for industry professionals and researchers in the fields of process safety, chemical safety, occupational and environmental health, and industrial hygiene.

Author : Jon Paul Janet
Publisher : American Chemical Society
ISBN 13 : 0841299005
Total Pages : 189 pages
Book Rating : 4.09/5 ( download)

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Download or read book Machine Learning in Chemistry written by Jon Paul Janet and published by American Chemical Society. This book was released on 2020-05-28 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important

Author : Alexander Heifetz
Publisher :
ISBN 13 : 9781071617878
Total Pages : 529 pages
Book Rating : 4.77/5 ( download)

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Download or read book Artificial Intelligence in Drug Design written by Alexander Heifetz and published by . This book was released on 2021 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary software and tools, step-by-step, readily reproducible modeling protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and unique, Artificial Intelligence in Drug Design is a valuable resource for structural and molecular biologists, computational and medicinal chemists, pharmacologists and drug designers.

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.94/5 ( download)

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Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Edward O. Pyzer-Knapp
Publisher :
ISBN 13 : 9780841235052
Total Pages : 140 pages
Book Rating : 4.58/5 ( download)

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Download or read book Machine Learning in Chemistry written by Edward O. Pyzer-Knapp and published by . This book was released on 2020-10-22 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Atomic-scale representation and statistical learning of tensorial properties -- Prediction of Mohs hardness with machine learning methods using compositional features -- High-dimensional neural network potentials for atomistic simulations -- Data-driven learning systems for chemical reaction prediction: an analysis of recent approaches -- Using machine learning to inform decisions in drug discovery : an industry perspective -- Cognitive materials discovery and onset of the 5th discovery paradigm.

Author : Hugh M. Cartwright
Publisher : Royal Society of Chemistry
ISBN 13 : 1788017897
Total Pages : 564 pages
Book Rating : 4.93/5 ( download)

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Download or read book Machine Learning in Chemistry written by Hugh M. Cartwright and published by Royal Society of Chemistry. This book was released on 2020-07-15 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.

Author : El Kacimi, Younes
Publisher : IGI Global
ISBN 13 :
Total Pages : 453 pages
Book Rating : 4.67/5 ( download)

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Download or read book Emerging Engineering Technologies and Industrial Applications written by El Kacimi, Younes and published by IGI Global. This book was released on 2024-05-06 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: Engineers have long been architects of progress, erecting massive buildings that touch the skies and designing technologies that redefine realms of known possibility. In this era of rapid change, keeping pace with innovation is the main challenge. Emerging Engineering Technologies and Industrial Applications is a comprehensive research book that delves deep into the heart of a relentless technological revolution within modern industry. From the limitless potential of the Internet of Things (IoT) to the cognitive wonders of Artificial Intelligence (AI), from the microscopic marvels of Nanotechnology to the precision and agility of Robotics, and from the revolutionary advancements in 3D Printing to the transformative capabilities of blockchain, this book explores emerging technologies. This book is an indispensable resource for professionals and researchers working in the field of emerging engineering technologies and their industrial applications. It caters to a diverse range of disciplines, including computer science and information technology, environmental, agricultural, and physical sciences, medical, healthcare, and life sciences, as well as science and engineering, and anyone seeking to navigate the current technological progress in the 21st century.

Author : Xiaowei Huang
Publisher : Springer Nature
ISBN 13 : 9811968144
Total Pages : 319 pages
Book Rating : 4.43/5 ( download)

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Download or read book Machine Learning Safety written by Xiaowei Huang and published by Springer Nature. This book was released on 2023-04-28 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises new safety concerns, as machine learning has many specificities that make its behaviour prediction and assessment very different from that for explicitly programmed software systems. This book addresses the main safety concerns with regard to machine learning, including its susceptibility to environmental noise and adversarial attacks. Such vulnerabilities have become a major roadblock to the deployment of machine learning in safety-critical applications. The book presents up-to-date techniques for adversarial attacks, which are used to assess the vulnerabilities of machine learning models; formal verification, which is used to determine if a trained machine learning model is free of vulnerabilities; and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readers’ awareness of the potential safety issues regarding machine learning models. In addition, it includes up-to-date techniques for dealing with these issues, equipping readers with not only technical knowledge but also hands-on practical skills.

Author : KC Santosh
Publisher : Springer Nature
ISBN 13 : 9811667683
Total Pages : 93 pages
Book Rating : 4.88/5 ( download)

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Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh and published by Springer Nature. This book was released on 2022-01-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.