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
Publsiher: Academic Press
Total Pages: 264
Release: 2021-04-23
ISBN 10: 0128204494
ISBN 13: 9780128204498
Language: EN, FR, DE, ES & NL

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

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 Drug Discovery

Artificial Intelligence in Drug Discovery
Author: Nathan Brown
Publsiher: Royal Society of Chemistry
Total Pages: 406
Release: 2020-11-11
ISBN 10: 1839160543
ISBN 13: 9781839160547
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Drug Discovery Book Review:

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 Pharmaceutical Sciences Drug Discovery

Artificial Intelligence in Pharmaceutical Sciences  Drug Discovery
Author: Dr Amit Gangwal
Publsiher: Unknown
Total Pages: 558
Release: 2020-08
ISBN 10: 1928374650XXX
ISBN 13: 9798551620655
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Pharmaceutical Sciences Drug Discovery Book Review:

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 pharmacy, nursing or medical courses. By the time it becomes part of syllabus, this book is among the best resources in a compiled format for healthcare professionals, academicians and students of pharmacy besides those want to learn from the basic; as content beyond syllabus tool. All the content has been compiled after referring and mining hundreds of latest and original first-hand updates from inventors, experts, organizations (who/which are engaged in drug discovery research directly or indirectly through Artificial Intelligence) like Insilico, Google, Microsoft, INVIDIA, Novartis, Intel, IBM etc. All topics are explained in very simple language with clear aim and outcome using flow charts, tables and infographics of original creators. Professionals from medical, pharmacy, nursing and dental and medical imaging arena will find this book very useful. Students of all levels will find book very beneficial as few topics have been just touched, few have been shallow in complexity and rest are covered in detail. Full precautions have been exercised to address the needs of biology group students so that they can easily and effortlessly understand the subject matter of this book, which requires mathematical skills to grasp the basics of AI. Recent examples from various corporates, universities and daily life have found place in this unique book in a very explicit manner. In initial two chapters, background information has been explained with various comparison and examples, while third chapter focuses on application of Artificial Intelligence in drug discovery, repurposing, in advance, faster and accurate diagnosis of diseases. Last chapter throws a light on insights pertaining to ethical issues in AI research; and laws related to intellectual property rights on products/services borne owing to success (partly or purely and fully) derived by machines or devices through AI programs/algorithms. At the end of each chapter, questions have been added for the readers, mainly students.

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
Publsiher: Academic Press
Total Pages: 290
Release: 2021-04-26
ISBN 10: 012823217X
ISBN 13: 9780128232170
Language: EN, FR, DE, ES & NL

Machine Learning and the Internet of Medical Things in Healthcare Book Review:

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 Machine Learning and Data Science Technologies

Artificial Intelligence  Machine Learning  and Data Science Technologies
Author: Neeraj Mohan,Ruchi Singla,Priyanka Kaushal,Seifedine Kadry
Publsiher: CRC Press
Total Pages: 310
Release: 2021-10-12
ISBN 10: 1000460541
ISBN 13: 9781000460544
Language: EN, FR, DE, ES & NL

Artificial Intelligence Machine Learning and Data Science Technologies Book Review:

This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr,Kaveh Memarzadeh
Publsiher: Academic Press
Total Pages: 378
Release: 2020-06-21
ISBN 10: 0128184396
ISBN 13: 9780128184394
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Healthcare Book Review:

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

Data Analytics in Bioinformatics
Author: Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
Publsiher: John Wiley & Sons
Total Pages: 544
Release: 2021-01-20
ISBN 10: 111978560X
ISBN 13: 9781119785606
Language: EN, FR, DE, ES & NL

Data Analytics in Bioinformatics Book Review:

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 for Drug Development Precision Medicine and Healthcare

Artificial Intelligence for Drug Development  Precision Medicine  and Healthcare
Author: Mark Chang
Publsiher: CRC Press
Total Pages: 352
Release: 2020-05-12
ISBN 10: 1000767302
ISBN 13: 9781000767308
Language: EN, FR, DE, ES & NL

Artificial Intelligence for Drug Development Precision Medicine and Healthcare Book Review:

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 in Oncology Drug Discovery and Development

Artificial Intelligence in Oncology Drug Discovery and Development
Author: John Cassidy,Belle Taylor
Publsiher: BoD – Books on Demand
Total Pages: 192
Release: 2020-09-09
ISBN 10: 1789846897
ISBN 13: 9781789846898
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Oncology Drug Discovery and Development Book Review:

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.

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
Publsiher: Elsevier
Total Pages: 540
Release: 2021-06-05
ISBN 10: 012821743X
ISBN 13: 9780128217436
Language: EN, FR, DE, ES & NL

Applications of Artificial Intelligence in Process Systems Engineering Book Review:

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 areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering

Smart Manufacturing

Smart Manufacturing
Author: Tan Yen Kheng
Publsiher: BoD – Books on Demand
Total Pages: 158
Release: 2021-01-14
ISBN 10: 1838810870
ISBN 13: 9781838810870
Language: EN, FR, DE, ES & NL

Smart Manufacturing Book Review:

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.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Parag Mahajan
Publsiher: Medmantra, LLC
Total Pages: 628
Release: 2021-02
ISBN 10: 9781954612020
ISBN 13: 1954612028
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Healthcare Book Review:

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 and Intelligent Medicine Simplified for Everyone ◆, you can discover the great improvements that AI is making, with chapters covering: The current applications and future of AI in healthcare and all major medical specialties ✓ The benefits and risks weighed up ✓ The ethics involved ✓ Machine learning and data science simplified ✓ AI's role in medical research and education, health insurance, drug discovery, electronic health records, and the fight against COVID-19 ✓ The roles that major corporations and start-up companies are playing ✓ The implementation of AI in clinical practice ✓ And lots more... Quite simply the most authoritative text on the subject, Artificial Intelligence in Healthcare - 3rd Edition, is an absorbing and compelling read for anyone who wants to know more. It is packed with more updated information than any other book currently available, written in easy-to-understand language, and accessible to all.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Lia Morra,Silvia Delsanto,Loredana Correale
Publsiher: CRC Press
Total Pages: 152
Release: 2019-11-25
ISBN 10: 1000753085
ISBN 13: 9781000753080
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging Book Review:

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 and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Machine Learning

Machine Learning
Author: Ryszard S. Michalski,Jaime G. Carbonell,Tom M. Mitchell
Publsiher: Elsevier
Total Pages: 572
Release: 2014-06-28
ISBN 10: 008051054X
ISBN 13: 9780080510545
Language: EN, FR, DE, ES & NL

Machine Learning Book Review:

Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs—particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV and V discuss learning from observation and discovery, and learning from instruction, respectively. Part VI presents two studies on applied learning systems—one on the recovery of valuable information via inductive inference; the other on inducing models of simple algebraic skills from observed student performance in the context of the Leeds Modeling System (LMS). This book is intended for researchers in artificial intelligence, computer science, and cognitive psychology; students in artificial intelligence and related disciplines; and a diverse range of readers, including computer scientists, robotics experts, knowledge engineers, educators, philosophers, data analysts, psychologists, and electronic engineers.

Artificial Intelligence Platform For Molecular Targeted Therapy A Translational Science Approach

Artificial Intelligence Platform For Molecular Targeted Therapy  A Translational Science Approach
Author: Ariel Fernandez
Publsiher: World Scientific
Total Pages: 468
Release: 2021-03-12
ISBN 10: 9811232326
ISBN 13: 9789811232329
Language: EN, FR, DE, ES & NL

Artificial Intelligence Platform For Molecular Targeted Therapy A Translational Science Approach Book Review:

In the era of big biomedical data, there are many ways in which artificial intelligence (AI) is likely to broaden the technological base of the pharmaceutical industry. Cheminformatic applications of AI involving the parsing of chemical space are already being implemented to infer compound properties and activity. By contrast, dynamic aspects of the design of drug/target interfaces have received little attention due to the inherent difficulties in dealing with physical phenomena that often do not conform to simplifying views.This book focuses precisely on dynamic drug/target interfaces and argues that the true game change in pharmaceutical discovery will come as AI is enabled to solve core problems in molecular biophysics that are intimately related to rational drug design and drug discovery.Here are a few examples to convey the flavor of our quest: How do we therapeutically impair a dysfunctional protein with unknown structure or regulation but known to be a culprit of disease? In regards to SARS-CoV-2, what is the structural impact of a dominant mutation?, how does the structure change translate into a fitness advantage?, what new therapeutic opportunity arises? How do we extend molecular dynamics simulations to realistic timescales, to capture the rare events associated with drug targeting in vivo? How do we control specificity in drug design to selectively remove side effects? This is the type of problems, directly related to the understanding of drug/target interfaces, that the book squarely addresses by leveraging a comprehensive AI-empowered approach.

Artificial Intelligence and Machine Learning for Business for Non Engineers

Artificial Intelligence and Machine Learning for Business for Non Engineers
Author: Stephan S. Jones,Frank M. Groom
Publsiher: CRC Press
Total Pages: 148
Release: 2019-12-18
ISBN 10: 1000733998
ISBN 13: 9781000733990
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Machine Learning for Business for Non Engineers Book Review:

The next big area within the information and communication technology field is Artificial Intelligence (AI). The industry is moving to automate networks, cloud-based systems (e.g., Salesforce), databases (e.g., Oracle), AWS machine learning (e.g., Amazon Lex), and creating infrastructure that has the ability to adapt in real-time to changes and learn what to anticipate in the future. It is an area of technology that is coming faster and penetrating more areas of business than any other in our history. AI will be used from the C-suite to the distribution warehouse floor. Replete with case studies, this book provides a working knowledge of AI’s current and future capabilities and the impact it will have on every business. It covers everything from healthcare to warehousing, banking, finance and education. It is essential reading for anyone involved in industry.

Medical Applications of Artificial Intelligence

Medical Applications of Artificial Intelligence
Author: Arvin Agah
Publsiher: CRC Press
Total Pages: 526
Release: 2013-11-06
ISBN 10: 143988434X
ISBN 13: 9781439884348
Language: EN, FR, DE, ES & NL

Medical Applications of Artificial Intelligence Book Review:

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Applications of Artificial Intelligence reviews the research, focusing on state-of-the-art projects in the field. The book captures the breadth and depth of the medical applications of artificial intelligence, exploring new developments and persistent challenges.

Introduction to Artificial Intelligence

Introduction to Artificial Intelligence
Author: Mariusz Flasiński
Publsiher: Springer
Total Pages: 321
Release: 2016-08-31
ISBN 10: 3319400223
ISBN 13: 9783319400228
Language: EN, FR, DE, ES & NL

Introduction to Artificial Intelligence Book Review:

In the chapters in Part I of this textbook the author introduces the fundamental ideas of artificial intelligence and computational intelligence. In Part II he explains key AI methods such as search, evolutionary computing, logic-based reasoning, knowledge representation, rule-based systems, pattern recognition, neural networks, and cognitive architectures. Finally, in Part III, he expands the context to discuss theories of intelligence in philosophy and psychology, key applications of AI systems, and the likely future of artificial intelligence. A key feature of the author's approach is historical and biographical footnotes, stressing the multidisciplinary character of the field and its pioneers. The book is appropriate for advanced undergraduate and graduate courses in computer science, engineering, and other applied sciences, and the appendices offer short formal, mathematical models and notes to support the reader.

Intelligent Decision Support Systems A Journey to Smarter Healthcare

Intelligent Decision Support Systems   A Journey to Smarter Healthcare
Author: Smaranda Belciug,Florin Gorunescu
Publsiher: Springer
Total Pages: 271
Release: 2019-03-20
ISBN 10: 3030143546
ISBN 13: 9783030143541
Language: EN, FR, DE, ES & NL

Intelligent Decision Support Systems A Journey to Smarter Healthcare Book Review:

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 and Deep Learning in Pathology

Artificial Intelligence and Deep Learning in Pathology
Author: Stanley Cohen
Publsiher: Elsevier Health Sciences
Total Pages: 288
Release: 2020-06-02
ISBN 10: 0323675379
ISBN 13: 9780323675376
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Deep Learning in Pathology Book Review:

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 nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.