The Era Of Artificial Intelligence Machine Learning And Data Science In The Pharmaceutical Industry

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

Author : Stephanie K. Ashenden
Publisher : Academic Press
ISBN 13 : 0128204494
Total Pages : 266 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry by : Stephanie K. Ashenden

Download or read book The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry written by Stephanie K. Ashenden and published by Academic Press. This book was released on 2021-04-23 with total page 266 pages. Available in PDF, EPUB and Kindle. Book 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

Author : Adam Bohr
Publisher : Academic Press
ISBN 13 : 0128184396
Total Pages : 385 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr

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

Data Analytics in Bioinformatics

Author : Rabinarayan Satpathy
Publisher : John Wiley & Sons
ISBN 13 : 111978560X
Total Pages : 433 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Data Analytics in Bioinformatics by : Rabinarayan Satpathy

Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 433 pages. Available in PDF, EPUB and Kindle. Book 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.

Artificial Intelligence in Drug Discovery

Author : Nathan Brown
Publisher : Royal Society of Chemistry
ISBN 13 : 1839160543
Total Pages : 425 pages
Book Rating : 4.8/5 (391 download)

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Book Synopsis Artificial Intelligence in Drug Discovery by : Nathan Brown

Download or read book Artificial Intelligence in Drug Discovery written by Nathan Brown and published by Royal Society of Chemistry. This book was released on 2020-11-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book 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.

Encyclopedia of Data Science and Machine Learning

Author : Wang, John
Publisher : IGI Global
ISBN 13 : 1799892212
Total Pages : 3296 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Encyclopedia of Data Science and Machine Learning by : Wang, John

Download or read book Encyclopedia of Data Science and Machine Learning written by Wang, John and published by IGI Global. This book was released on 2023-01-20 with total page 3296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Machine Learning in Industry

Author : Shubhabrata Datta
Publisher : Springer Nature
ISBN 13 : 3030758478
Total Pages : 202 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Machine Learning in Industry by : Shubhabrata Datta

Download or read book Machine Learning in Industry written by Shubhabrata Datta and published by Springer Nature. This book was released on 2021-07-24 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.

Artificial Intelligence and Industry 4.0

Author : Aboul Ella Hassanien
Publisher : Academic Press
ISBN 13 : 0323906397
Total Pages : 264 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Artificial Intelligence and Industry 4.0 by : Aboul Ella Hassanien

Download or read book Artificial Intelligence and Industry 4.0 written by Aboul Ella Hassanien and published by Academic Press. This book was released on 2022-08-14 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Industry 4.0 explores recent advancements in blockchain technology and artificial intelligence (AI) as well as their crucial impacts on realizing Industry 4.0 goals. The book explores AI applications in industry including Internet of Things (IoT) and Industrial Internet of Things (IIoT) technology. Chapters explore how AI (machine learning, smart cities, healthcare, Society 5.0, etc.) have numerous potential applications in the Industry 4.0 era. This book is a useful resource for researchers and graduate students in computer science researching and developing AI and the IIoT. - Explores artificial intelligence applications within the industrial manufacturing and communications sectors - Presents a wide range of machine learning, computer vision, and digital twin applications across the IoT sector - Explores how deep learning and cognitive computing tools enable processing vast data sets, precise and comprehensive forecast of risks, and delivering recommended actions

Artificial Intelligence in Drug Design

Author : Alexander Heifetz
Publisher : Humana
ISBN 13 : 9781071617892
Total Pages : 0 pages
Book Rating : 4.6/5 (178 download)

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Book Synopsis Artificial Intelligence in Drug Design by : Alexander Heifetz

Download or read book Artificial Intelligence in Drug Design written by Alexander Heifetz and published by Humana. This book was released on 2022-11-05 with total page 0 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.

Intelligent Decision Support Systems—A Journey to Smarter Healthcare

Author : Smaranda Belciug
Publisher : Springer
ISBN 13 : 3030143546
Total Pages : 282 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Intelligent Decision Support Systems—A Journey to Smarter Healthcare by : Smaranda Belciug

Download or read book Intelligent Decision Support Systems—A Journey to Smarter Healthcare written by Smaranda Belciug and published by Springer. This book was released on 2019-03-20 with total page 282 pages. Available in PDF, EPUB and Kindle. Book 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.

De novo Molecular Design

Author : Gisbert Schneider
Publisher : John Wiley & Sons
ISBN 13 : 3527677038
Total Pages : 540 pages
Book Rating : 4.5/5 (276 download)

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Book Synopsis De novo Molecular Design by : Gisbert Schneider

Download or read book De novo Molecular Design written by Gisbert Schneider and published by John Wiley & Sons. This book was released on 2013-10-10 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, Proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules. A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for chemical probes and diagnostics, pesticides, and any other molecule designed to interact with a biological system. Numerous images and screenshots illustrate the many examples and method descriptions. With its broad and balanced coverage, this will be the firststop resource not only for medicinal chemists, biochemists and biotechnologists, but equally for bioinformaticians and molecular designers for many years to come. From the content: * Reaction-driven de novo design * Adaptive methods in molecular design * Design of ligands against multitarget profiles * Free energy methods in ligand design * Fragment-based de novo design * Automated design of focused and target family-oriented compound libraries * Molecular de novo design by nature-inspired computing * 3D QSAR approaches to de novo drug design * Bioisosteres in de novo design * De novo design of peptides, proteins and nucleic acid structures, including RNA aptamers and many more.

Practical Deep Learning for Cloud, Mobile, and Edge

Author : Anirudh Koul
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492034819
Total Pages : 585 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Practical Deep Learning for Cloud, Mobile, and Edge by : Anirudh Koul

Download or read book Practical Deep Learning for Cloud, Mobile, and Edge written by Anirudh Koul and published by "O'Reilly Media, Inc.". This book was released on 2019-10-14 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

Deep Learning for the Life Sciences

Author : Bharath Ramsundar
Publisher : O'Reilly Media
ISBN 13 : 1492039802
Total Pages : 236 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for the Life Sciences by : Bharath Ramsundar

Download or read book Deep Learning for the Life Sciences written by Bharath Ramsundar and published by O'Reilly Media. This book was released on 2019-04-10 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working

Artificial Intelligence in Medicine

Author : David Riaño
Publisher : Springer
ISBN 13 : 303021642X
Total Pages : 431 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Artificial Intelligence in Medicine by : David Riaño

Download or read book Artificial Intelligence in Medicine written by David Riaño and published by Springer. This book was released on 2019-06-19 with total page 431 pages. Available in PDF, EPUB and Kindle. Book 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.

AI to machine learning in Pharmaceuticals

Author : Satyabrata Jena
Publisher : AG PUBLISHING HOUSE (AGPH Books)
ISBN 13 : 9395936754
Total Pages : 224 pages
Book Rating : 4.3/5 (959 download)

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Book Synopsis AI to machine learning in Pharmaceuticals by : Satyabrata Jena

Download or read book AI to machine learning in Pharmaceuticals written by Satyabrata Jena and published by AG PUBLISHING HOUSE (AGPH Books). This book was released on 2022-11-16 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The convergence of big data, artificial intelligence (AI), and machine learning (ML) has resulted in a paradigm change in the manner in which novel medications are generated and healthcare is given. It is vital to systematically harness data from varied sources and utilize digital technologies and sophisticated analytics in order to allow data-driven decision making in order to fully capitalize on the breakthroughs in technology that have been made in recent years. The field of data science is now in a position where it has an unparalleled chance to steer such a paradigm shift. This book provides a high-level overview of fundamental concepts in algorithmic theory, data representation techniques, and generative modelling. Use the discovery of antibiotics as a case study in machine learning applied to the production of drugs, and then examine several applications in drug-likeness prediction, antimicrobial resistance, & avenues for further investigation. In the most recent years, there has been a marked increase in the application of machine learning algorithms to the process of drug discovery, and this book offers a comprehensive overview of the rapidly developing field. An introduction to the ways in which machine learning iv and artificial intelligence are being used in the pharmaceutical industry. The introductory discussion focuses on the use of machine learning to better understand medication-target interactions as a means of enhancing drug delivery as well as healthcare and medical systems. In addition to this, give subjects on medication repurposing using machine learning, drug designing, and finally, address drug combinations that are recommended to patients who have several or complicated diseases.

The Democratization of Artificial Intelligence

Author : Andreas Sudmann
Publisher : transcript Verlag
ISBN 13 : 3839447194
Total Pages : 335 pages
Book Rating : 4.8/5 (394 download)

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Book Synopsis The Democratization of Artificial Intelligence by : Andreas Sudmann

Download or read book The Democratization of Artificial Intelligence written by Andreas Sudmann and published by transcript Verlag. This book was released on 2019-10-31 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: After a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms?

Artificial intelligence in Pharmaceutical Sciences

Author : Mullaicharam Bhupathyraaj
Publisher : CRC Press
ISBN 13 : 1000994554
Total Pages : 181 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Artificial intelligence in Pharmaceutical Sciences by : Mullaicharam Bhupathyraaj

Download or read book Artificial intelligence in Pharmaceutical Sciences written by Mullaicharam Bhupathyraaj and published by CRC Press. This book was released on 2023-11-23 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge reference book discusses the intervention of artificial intelligence in the fields of drug development, modified drug delivery systems, pharmaceutical technology, and medical devices development. This comprehensive book includes an overview of artificial intelligence in pharmaceutical sciences and applications in the drug discovery and development process. It discusses the role of machine learning in the automated detection and sorting of pharmaceutical formulations. It covers nanosafety and the role of artificial intelligence in predicting potential adverse biological effects. FEATURES Includes lucid, step-by-step instructions to apply artificial intelligence and machine learning in pharmaceutical sciences Explores the application of artificial intelligence in nanosafety and prediction of potential hazards Covers application of artificial intelligence in drug discovery and drug development Reviews the role of artificial intelligence in assessment of pharmaceutical formulations Provides artificial intelligence solutions for experts in the pharmaceutical and medical devices industries This book is meant for academicians, students, and industry experts in pharmaceutical sciences, medicine, and pharmacology.

Handbook of Research on AI and ML for Intelligent Machines and Systems

Author : Gupta, Brij B.
Publisher : IGI Global
ISBN 13 :
Total Pages : 530 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Handbook of Research on AI and ML for Intelligent Machines and Systems by : Gupta, Brij B.

Download or read book Handbook of Research on AI and ML for Intelligent Machines and Systems written by Gupta, Brij B. and published by IGI Global. This book was released on 2023-11-27 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths.