The Era of Artificial Intelligence  Machine Learning  and Data Science in the Pharmaceutical Industry Book

The Era of Artificial Intelligence Machine Learning and Data Science in the Pharmaceutical Industry


  • Author : Stephanie K. Ashenden
  • Publisher : Academic Press
  • Release Date : 2021-04-23
  • Genre: Computers
  • Pages : 264
  • ISBN 10 : 9780128204498

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The Era of Artificial Intelligence Machine Learning and Data Science in the Pharmaceutical Industry Excerpt :

The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics. Demonstrates how the prediction of toxic effects is performed, how to reduce costs in testing compounds, and its use in animal research Written by the industrial teams who are conducting the work, showcasing how the technology has improved and where it should be further improved Targets materials for a better understanding of techniques from different disciplines, thus creating a complete guide

Artificial Intelligence in Healthcare Book

Artificial Intelligence in Healthcare


  • Author : Adam Bohr
  • Publisher : Academic Press
  • Release Date : 2020-06-21
  • Genre: Computers
  • Pages : 378
  • ISBN 10 : 9780128184394

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Artificial Intelligence in Healthcare 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

Artificial Intelligence in Drug Discovery Book

Artificial Intelligence in Drug Discovery


  • Author : Nathan Brown
  • Publisher : Royal Society of Chemistry
  • Release Date : 2020-11-11
  • Genre: Computers
  • Pages : 406
  • ISBN 10 : 9781839160547

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Artificial Intelligence in Drug Discovery Excerpt :

Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.

Artificial Intelligence in Medicine Book

Artificial Intelligence in Medicine


  • Author : David Riaño
  • Publisher : Springer
  • Release Date : 2019-06-19
  • Genre: Computers
  • Pages : 429
  • ISBN 10 : 9783030216429

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Artificial Intelligence in Medicine Excerpt :

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Artificial Intelligence in Drug Design Book

Artificial Intelligence in Drug Design


  • Author : Alexander Heifetz
  • Publisher : Humana
  • Release Date : 2021-11-04
  • Genre: Medical
  • Pages : 529
  • ISBN 10 : 1071617869

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Artificial Intelligence in Drug Design 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.

Data Analytics in Bioinformatics Book

Data Analytics in Bioinformatics


  • Author : Rabinarayan Satpathy
  • Publisher : John Wiley & Sons
  • Release Date : 2021-01-20
  • Genre: Computers
  • Pages : 544
  • ISBN 10 : 9781119785606

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Data Analytics in Bioinformatics Excerpt :

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Machine Learning and the Internet of Medical Things in Healthcare Book

Machine Learning and the Internet of Medical Things in Healthcare


  • Author : Krishna Kant Singh
  • Publisher : Academic Press
  • Release Date : 2021-04-26
  • Genre: Science
  • Pages : 290
  • ISBN 10 : 9780128232170

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Machine Learning and the Internet of Medical Things in Healthcare Excerpt :

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Artificial Intelligence in Oncology Drug Discovery and Development Book

Artificial Intelligence in Oncology Drug Discovery and Development


  • Author : John Cassidy
  • Publisher : BoD – Books on Demand
  • Release Date : 2020-09-09
  • Genre: Medical
  • Pages : 194
  • ISBN 10 : 9781789846898

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Artificial Intelligence in Oncology Drug Discovery and Development Excerpt :

There exists a profound conflict at the heart of oncology drug development. The efficiency of the drug development process is falling, leading to higher costs per approved drug, at the same time personalised medicine is limiting the target market of each new medicine. Even as the global economic burden of cancer increases, the current paradigm in drug development is unsustainable. In this book, we discuss the development of techniques in machine learning for improving the efficiency of oncology drug development and delivering cost-effective precision treatment. We consider how to structure data for drug repurposing and target identification, how to improve clinical trials and how patients may view artificial intelligence.

Artificial Intelligence for Drug Development  Precision Medicine  and Healthcare Book

Artificial Intelligence for Drug Development Precision Medicine and Healthcare


  • Author : Mark Chang
  • Publisher : CRC Press
  • Release Date : 2020-05-12
  • Genre: Business & Economics
  • Pages : 235
  • ISBN 10 : 9781000767308

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Artificial Intelligence for Drug Development Precision Medicine and Healthcare Excerpt :

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.

Artificial Intelligence and Machine Learning for Healthcare Book

Artificial Intelligence and Machine Learning for Healthcare


  • Author : Chee Peng Lim
  • Publisher : Springer Nature
  • Release Date : 2022-09-29
  • Genre: Medical
  • Pages : 282
  • ISBN 10 : 9783031111709

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Artificial Intelligence and Machine Learning for Healthcare Excerpt :

In line with advances in digital and computing systems, artificial intelligence (AI) and machine learning (ML) technologies have transformed many aspects of medical and healthcare services, delivering tangible benefits to patents and the general public. This book is a sequel of the edition on “Artificial Intelligence and Machine Learning for Healthcare”. The first volume is focused on utilization of AI and ML for image and data analytics in the medical and healthcare domains. In this second volume, emerging methodologies and future trends in AI and ML for advancing medical treatments and healthcare services are presented. The selected studies in this book provide readers a glimpse on current progresses in AI and ML for undertaking a variety of healthcare-related tasks. The advances in AI and ML technologies for future healthcare are also discussed, shedding light on the potential of AI and ML to realize the next-generation medical treatments and healthcare services for the betterment of our global society.

Intelligent Decision Support Systems   A Journey to Smarter Healthcare Book

Intelligent Decision Support Systems A Journey to Smarter Healthcare


  • Author : Smaranda Belciug
  • Publisher : Springer
  • Release Date : 2019-03-20
  • Genre: Technology & Engineering
  • Pages : 271
  • ISBN 10 : 9783030143541

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Intelligent Decision Support Systems A Journey to Smarter Healthcare Excerpt :

The goal of this book is to provide, in a friendly and refreshing manner, both theoretical concepts and practical techniques for the important and exciting field of Artificial Intelligence that can be directly applied to real-world healthcare problems. Healthcare – the final frontier. Lately, it seems like Pandora opened the box and evil was released into the world. Fortunately, there was one thing left in the box: hope. In recent decades, hope has been increasingly represented by Intelligent Decision Support Systems. Their continuing mission: to explore strange new diseases, to seek out new treatments and drugs, and to intelligently manage healthcare resources and patients. Hence, this book is designed for all those who wish to learn how to explore, analyze and find new solutions for the most challenging domain of all time: healthcare.

Artificial Intelligence in Medical Imaging Book

Artificial Intelligence in Medical Imaging


  • Author : Erik R. Ranschaert
  • Publisher : Springer
  • Release Date : 2019-01-29
  • Genre: Medical
  • Pages : 373
  • ISBN 10 : 9783319948782

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Artificial Intelligence in Medical Imaging Excerpt :

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.

Machine Learning for Critical Internet of Medical Things Book

Machine Learning for Critical Internet of Medical Things


  • Author : Fadi Al-Turjman
  • Publisher : Springer Nature
  • Release Date : 2022
  • Genre: Artificial intelligence
  • Pages : 267
  • ISBN 10 : 9783030809287

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Machine Learning for Critical Internet of Medical Things Excerpt :

This book discusses the applications, challenges, and future trends of machine learning in medical domain, including both basic and advanced topics. The book presents how machine learning is helpful in smooth conduction of administrative processes in hospitals, in treating infectious diseases, and in personalized medical treatments. The authors show how machine learning can also help make fast and more accurate disease diagnoses, easily identify patients, help in new types of therapies or treatments, model small-molecule drugs in pharmaceutical sector, and help with innovations via integrated technologies such as artificial intelligence as well as deep learning. The authors show how machine learning also improves the physicians and doctors medical capabilities to better diagnosis their patients. This book illustrates advanced, innovative techniques, frameworks, concepts, and methodologies of machine learning that will enhance the efficiency and effectiveness of the healthcare system. Provides researchers in machine and deep learning with a conceptual understanding of various methodologies of implementing the technologies in medical areas; Discusses the role machine learning and IoT play into locating different virus and diseases across the globe, such as COVID-19, Ebola, and cervical cancer; Includes fundamentals and advances in machine learning in the medical field, supported by significant case studies and practical applications.

Applications of Machine Learning Book
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Applications of Machine Learning


  • Author : Prashant Johri
  • Publisher : Springer Nature
  • Release Date : 2020-05-04
  • Genre: Technology & Engineering
  • Pages : 394
  • ISBN 10 : 9789811533570

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Applications of Machine Learning Excerpt :

This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

AI and education Book

AI and education


  • Author : Miao, Fengchun
  • Publisher : UNESCO Publishing
  • Release Date : 2021-04-08
  • Genre: Political Science
  • Pages : 50
  • ISBN 10 : 9789231004476

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AI and education Excerpt :

Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed]