Precision Medicine and Artificial Intelligence

Precision Medicine and Artificial Intelligence
Author: Michael Mahler
Publsiher: Elsevier
Total Pages: 300
Release: 2021-04-15
ISBN 10: 0128202394
ISBN 13: 9780128202395
Language: EN, FR, DE, ES & NL

Precision Medicine and Artificial Intelligence Book Review:

Precision Medicine and Artificial Intelligence: The Perfect Fit for Autoimmunity covers background on AI, its link to PM, and examples of AI in healthcare, especially autoimmunity. The book highlights future perspectives and potential directions as artificial intelligence (AI) has gained significant attention in the past decade. Autoimmune diseases are complex and heterogeneous conditions, but exciting new developments and implementation tactics surrounding automated systems has enabled the generation of large amounts of data, making autoimmunity an ideal target for AI in the field of Precision Medicine (PM). More and more diagnostic products utilize AI, which is also starting to be supported by regulatory agencies such as the Food and Drug Administration (FDA). Knowledge generation by leveraging large data sets including demographic, environmental, clinical and biomarker data has the potential to not only impact the diagnosis of patients, but also disease prediction, prognosis and treatment options. Allows the readers to get a good overview of the field of Precision Medicine for autoimmune diseases and Artificial Intelligence Provides background, milestone and examples of precision medicine for autoimmune disease and artificial intelligence Proves the paradigm shift towards precision medicine driven by value-based systems Discusses future applications of precision medicine research using artificial intelligence

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 Precision Health

Artificial Intelligence in Precision Health
Author: Debmalya Barh
Publsiher: Academic Press
Total Pages: 544
Release: 2020-03-04
ISBN 10: 0128173386
ISBN 13: 9780128173381
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Precision Health Book Review:

Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available. This book is a valuable source for clinicians, healthcare workers, and researchers from diverse areas of biomedical field who may or may not have computational background and want to learn more about the innovative field of artificial intelligence for precision health. Provides computational approaches used in artificial intelligence easily understandable for non-computer specialists Gives know-how and real successful cases of artificial intelligence approaches in predictive models, modeling disease physiology, and public health surveillance Discusses the applicability of AI on multiple areas, such as drug discovery, clinical trials, radiology, surgery, patient care and clinical decision support

Artificial Intelligence and Machine Learning in Healthcare

Artificial Intelligence and Machine Learning in Healthcare
Author: Ankur Saxena,Shivani Chandra
Publsiher: Springer Nature
Total Pages: 228
Release: 2021-05-06
ISBN 10: 9811608113
ISBN 13: 9789811608117
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Machine Learning in Healthcare Book Review:

This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Lei Xing,Maryellen L. Giger,James K. Min
Publsiher: Academic Press
Total Pages: 568
Release: 2020-09-03
ISBN 10: 0128212586
ISBN 13: 9780128212585
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Review:

Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

Precision Medicine in Cardiovascular Disease Prevention

Precision Medicine in Cardiovascular Disease Prevention
Author: Seth S. Martin
Publsiher: Springer Nature
Total Pages: 194
Release: 2021-07-07
ISBN 10: 3030750558
ISBN 13: 9783030750558
Language: EN, FR, DE, ES & NL

Precision Medicine in Cardiovascular Disease Prevention Book Review:

This book contains the current knowledge and potential future developments of precision medicine techniques including artificial intelligence, big data, mobile health, digital health and genetic medicine in the prevention of cardiovascular disease. It reviews the presently used advanced precision medicine techniques and fundamental principles that continue to act as guiding forces for many medical professionals in applying precision and preventative medical techniques in their day-to-day practices. Precision Medicine in Cardiovascular Disease Prevention describes current knowledge and potential future developments in this rapidly expanding field. It therefore provides a valuable resource for all practicing and trainee cardiologists looking to develop their knowledge and integrate precision medicine techniques into their practices.

Biocomputing 2021 Proceedings Of The Pacific Symposium

Biocomputing 2021   Proceedings Of The Pacific Symposium
Author: Russ B Altman,A Keith Dunker,Lawrence Hunter,Marylyn D Ritchie,Tiffany A Murray,Teri E Klein
Publsiher: World Scientific
Total Pages: 380
Release: 2020-11-24
ISBN 10: 9811232717
ISBN 13: 9789811232718
Language: EN, FR, DE, ES & NL

Biocomputing 2021 Proceedings Of The Pacific Symposium Book Review:

The Pacific Symposium on Biocomputing (PSB) 2021 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2021 will be held on a virtual platform at psb.stanford.edu/ on January 5-7, 2021. Tutorials and workshops will be offered prior to the start of the conference.PSB 2021 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

Artificial Intelligence and Big Data Analytics for Smart Healthcare

Artificial Intelligence and Big Data Analytics for Smart Healthcare
Author: Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui
Publsiher: Academic Press
Total Pages: 290
Release: 2021-10-22
ISBN 10: 0128220627
ISBN 13: 9780128220627
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Big Data Analytics for Smart Healthcare Book Review:

Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers

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

Intelligent Communication and Automation Systems

Intelligent Communication and Automation Systems
Author: Kamal Kumar Sharma,Akhil Gupta,Bandana Sharma,Suman Lata Tripathi
Publsiher: CRC Press
Total Pages: 362
Release: 2021-04-19
ISBN 10: 1000372111
ISBN 13: 9781000372113
Language: EN, FR, DE, ES & NL

Intelligent Communication and Automation Systems Book Review:

This comprehensive reference text discusses concepts of intelligence communication and automation system in a single volume. The text discusses the role of artificial intelligence in communication engineering, the role of machine learning in communication systems, and applications of image and video processing in communication. It covers important topics including smart sensing systems, intelligent hardware design, low power system design using AI techniques, intelligent signal processing for biomedical applications, intelligent robotic systems, and network security applications. The text will be useful for senior undergraduate and graduate students in different areas including electrical engineering, and electronics and communications engineering.

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: 368
Release: 2020-02-12
ISBN 10: 9780367362928
ISBN 13: 0367362929
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 Healthcarecovers 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.

Precision Medicine in Cancer Therapy

Precision Medicine in Cancer Therapy
Author: Daniel D. Von Hoff,Haiyong Han
Publsiher: Springer
Total Pages: 283
Release: 2019-06-17
ISBN 10: 3030163911
ISBN 13: 9783030163914
Language: EN, FR, DE, ES & NL

Precision Medicine in Cancer Therapy Book Review:

This book presents the latest advances in precision medicine in some of the most common cancer types, including hematological, lung and breast malignancies. It also discusses emerging technologies that are making a significant impact on precision medicine in cancer therapy. In addition to describing specific approaches that have already entered clinical practice, the book explores new concepts and tools that are being developed. Precision medicine aims to deliver personalized healthcare tailored to a patient’s genetics, lifestyle and environment, and cancer therapy is one of the areas in which it has flourished in recent years. Documenting the latest advances, this book is of interest to physicians and clinical fellows in the front line of the war on cancer, as well as to basic scientists working in the fields of cancer biology, drug development, biomarker discovery, and biomedical engineering. The contributing authors include translational physicians with first-hand experience in precision patient care.

Deep Medicine

Deep Medicine
Author: Eric Topol
Publsiher: Basic Books
Total Pages: 400
Release: 2019-03-12
ISBN 10: 1541644646
ISBN 13: 9781541644649
Language: EN, FR, DE, ES & NL

Deep Medicine Book Review:

One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Explainable AI in Healthcare and Medicine

Explainable AI in Healthcare and Medicine
Author: Arash Shaban-Nejad,Martin Michalowski,David L. Buckeridge
Publsiher: Springer Nature
Total Pages: 344
Release: 2020-11-02
ISBN 10: 3030533522
ISBN 13: 9783030533526
Language: EN, FR, DE, ES & NL

Explainable AI in Healthcare and Medicine Book Review:

This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.

Machine Learning Advanced Dynamic Omics Data Analysis for Precision Medicine

Machine Learning Advanced Dynamic Omics Data Analysis for Precision Medicine
Author: Tao Zeng,Tao Huang,Chuan Lu
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2020-03-30
ISBN 10: 2889635546
ISBN 13: 9782889635542
Language: EN, FR, DE, ES & NL

Machine Learning Advanced Dynamic Omics Data Analysis for Precision Medicine Book Review:

Artificial Intelligence and Machine Learning in Public Healthcare

Artificial Intelligence and Machine Learning in Public Healthcare
Author: KC Santosh,Loveleen Gaur
Publsiher: Springer
Total Pages: 74
Release: 2021-11-27
ISBN 10: 9789811667671
ISBN 13: 9811667675
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Machine Learning in Public Healthcare Book Review:

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

Genetics and Genomics of Eye Disease

Genetics and Genomics of Eye Disease
Author: Xiaoyi Raymond Gao
Publsiher: Academic Press
Total Pages: 383
Release: 2019-09-12
ISBN 10: 0128167270
ISBN 13: 9780128167274
Language: EN, FR, DE, ES & NL

Genetics and Genomics of Eye Disease Book Review:

Genetics and Genomics of Eye Disease: Advancing to Precision Medicine thoroughly examines the latest genomics methods for studying eye disease, including complex eye disorders associated with multiple genes. GWAS, WES, WGS, RNA-sequencing, and transcriptome analysis as employed in ocular genomics are discussed in-depth, as are genomics findings tied to early-onset glaucoma, strabismus, age-related macular degeneration, adult-onset glaucoma, diabetic retinopathy, keratoconus, and leber congenital amaurosis, among other diseases. Research and clinical specialists offer guidance on conducting preventative screenings and counseling patients, as well as the promise of machine learning, computational statistics and artificial intelligence in advancing ocular genomics research. Offers thorough guidance on conducting genetic and genomic studies of eye disease Examines the genetic basis of a wide range of complex eye diseases and single-gene and Mendelian disorders Discusses the application of genetic testing and genetic risk prediction in eye disease diagnosis and patient counseling

Artificial Intelligence in Healthcare and Medicine

Artificial Intelligence in Healthcare and Medicine
Author: Kayvan Najarian,Delaram Kahrobaei,Enrique Domínguez,Reza Soroushmehr
Publsiher: Unknown
Total Pages: 286
Release: 2022
ISBN 10: 9781000565843
ISBN 13: 100056584X
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Healthcare and Medicine Book Review:

This book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
Author: Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
Publsiher: Academic Press
Total Pages: 454
Release: 2020-11-20
ISBN 10: 0128202742
ISBN 13: 9780128202746
Language: EN, FR, DE, ES & NL

Machine Learning in Cardiovascular Medicine Book Review:

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

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.