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

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

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  • Author : Stephanie K. Ashenden
  • Publisher : Academic Press
  • Pages : 264 pages
  • ISBN : 0128204494
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKThe Era of Artificial Intelligence Machine Learning and Data Science in the Pharmaceutical Industry

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

The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry
  • Author : Stephanie K. Ashenden
  • Publisher : Academic Press
  • Release : 23 April 2021
GET THIS BOOKThe Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry

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

Artificial Intelligence in Drug Discovery

Artificial Intelligence in Drug Discovery
  • Author : Nathan Brown
  • Publisher : Royal Society of Chemistry
  • Release : 11 November 2020
GET THIS BOOKArtificial Intelligence in Drug Discovery

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

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
  • Author : Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
  • Publisher : Academic Press
  • Release : 26 April 2021
GET THIS BOOKMachine Learning and the Internet of Medical Things in Healthcare

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

Artificial Intelligence in Pharmaceutical Sciences (Drug Discovery)

Artificial Intelligence in Pharmaceutical Sciences (Drug Discovery)
  • Author : Dr Amit Gangwal
  • Publisher : Unknown Publisher
  • Release : 01 August 2020
GET THIS BOOKArtificial Intelligence in Pharmaceutical Sciences (Drug Discovery)

The book has been designed to cover all the basic topics and examples related to disruptive innovations and industry 4.0 in general and in particular, pharmaceutical sciences and other branches of healthcare sectors like medical and diagnostic. Major disruption is due to the advent of Artificial Intelligence, Machine Learning, Deep Learning, Blockchain, 3D Organ Printing and others. The book is ahead of its time in the sense that in entire country there is no such subject which is being taught in

Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering
  • Author : Jingzheng Ren,Weifeng Shen,Yi Man,Lichun DOng
  • Publisher : Elsevier
  • Release : 05 June 2021
GET THIS BOOKApplications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
  • Author : Adam Bohr,Kaveh Memarzadeh
  • Publisher : Academic Press
  • Release : 21 June 2020
GET THIS BOOKArtificial Intelligence in Healthcare

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

Artificial Intelligence and Internet of Things

Artificial Intelligence and Internet of Things
  • Author : Lalit Mohan Goyal,Tanzila Saba,Amjad Rehman,Souad Larabi-Marie-Sainte
  • Publisher : CRC Press
  • Release : 25 August 2021
GET THIS BOOKArtificial Intelligence and Internet of Things

This book reveals the applications of AI and IoT in smart healthcare and medical systems. It provides core principles, algorithms, protocols, emerging trends, security problems, and the latest e-healthcare services findings. The book also provides case studies and discusses how AI and IoT applications such as wireless devices, sensors, and deep learning could play a major role in assisting patients, doctors, and pharmaceutical staff. It focuses on how to use AI and IoT to keep patients safe and healthy and,

Data Analytics in Bioinformatics

Data Analytics in Bioinformatics
  • Author : Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
  • Publisher : John Wiley & Sons
  • Release : 20 January 2021
GET THIS BOOKData Analytics in Bioinformatics

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

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
  • Author : Parag Mahajan
  • Publisher : Medmantra, LLC
  • Release : 01 February 2021
GET THIS BOOKArtificial Intelligence in Healthcare

① Do you know what AI is doing to improve our health and wellbeing? ② Does this new technology concern you, or impress you? ③ Do you want to know more about the future of AI in healthcare? Technology continues to advance at a pace that can seem bewildering. Nowhere else is it moving faster than in the health sector, where ♥AI is now being used to improve millions of lives♥. In this book, ◆ Artificial Intelligence in Healthcare: AI, Machine Learning, and Deep

Artificial Intelligence and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology
  • Author : Stanley Cohen
  • Publisher : Elsevier Health Sciences
  • Release : 02 June 2020
GET THIS BOOKArtificial Intelligence and Deep Learning in Pathology

Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the

Artificial Intelligence in Oncology Drug Discovery and Development

Artificial Intelligence in Oncology Drug Discovery and Development
  • Author : John Cassidy,Belle Taylor
  • Publisher : BoD – Books on Demand
  • Release : 09 September 2020
GET THIS BOOKArtificial Intelligence in Oncology Drug Discovery and Development

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

The Artificial Intelligence Infrastructure Workshop

The Artificial Intelligence Infrastructure Workshop
  • Author : Chinmay Arankalle,Gareth Dwyer,Bas Geerdink,Kunal Gera,Kevin Liao,Anand N.S.
  • Publisher : Packt Publishing Ltd
  • Release : 17 August 2020
GET THIS BOOKThe Artificial Intelligence Infrastructure Workshop

Explore how a data storage system works – from data ingestion to representation Key Features Understand how artificial intelligence, machine learning, and deep learning are different from one another Discover the data storage requirements of different AI apps using case studies Explore popular data solutions such as Hadoop Distributed File System (HDFS) and Amazon Simple Storage Service (S3) Book Description Social networking sites see an average of 350 million uploads daily - a quantity impossible for humans to scan and analyze. Only

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
  • Author : Lia Morra,Silvia Delsanto,Loredana Correale
  • Publisher : CRC Press
  • Release : 25 November 2019
GET THIS BOOKArtificial Intelligence in Medical Imaging

This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed

Smart Manufacturing

Smart Manufacturing
  • Author : Tan Yen Kheng
  • Publisher : BoD – Books on Demand
  • Release : 14 January 2021
GET THIS BOOKSmart Manufacturing

Smart manufacturing uses big data, the Internet of things (IoT) and the Internet of Services (IoS), and flexible and dynamic workforces to cope with ever-increasing demand in low-volume, high-mix production. Companies worldwide are already pivoting towards dynamic and reconfigurable production as a smarter way to build and make things. As such, this book discusses the next generation of manufacturing, which will involve the transformational convergence of intelligent machines, powerful computing and analytics, and unprecedented networking of people, products, and services.

Machine Learning for Healthcare Applications

Machine Learning for Healthcare Applications
  • Author : Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar
  • Publisher : John Wiley & Sons
  • Release : 04 May 2021
GET THIS BOOKMachine Learning for Healthcare Applications

When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health