Artificial Intelligence In Oncology Drug Discovery And Development
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Artificial Intelligence In Oncology Drug Discovery And Development
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Author : John Cassidy
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-09-09
Artificial Intelligence In Oncology Drug Discovery And Development written by John Cassidy and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-09 with Medical categories.
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 Machine Learning
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Author : Prashant Johri
language : en
Publisher: Springer Nature
Release Date : 2020-05-04
Applications Of Machine Learning written by Prashant Johri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-04 with Technology & Engineering categories.
This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
Healthcare And Artificial Intelligence
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Author : Bernard Nordlinger
language : en
Publisher: Springer Nature
Release Date : 2020-03-17
Healthcare And Artificial Intelligence written by Bernard Nordlinger and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-17 with Technology & Engineering categories.
This book provides an overview of the role of AI in medicine and, more generally, of issues at the intersection of mathematics, informatics, and medicine. It is intended for AI experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious about this timely and important subject. Its goal is to provide clear, objective, and reasonable information on the issues covered, avoiding any fantasies that the topic “AI” might evoke. In addition, the book seeks to provide a broad kaleidoscopic perspective, rather than deep technical details.
Artificial Intelligence In Healthcare
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Author : Adam Bohr
language : en
Publisher: Academic Press
Release Date : 2020-06-21
Artificial Intelligence In Healthcare written by Adam Bohr and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-21 with Computers categories.
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
Antibody Drug Conjugates
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Author : Kenneth J. Olivier, Jr.
language : en
Publisher: John Wiley & Sons
Release Date : 2016-11-14
Antibody Drug Conjugates written by Kenneth J. Olivier, Jr. and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-14 with Medical categories.
Providing practical and proven solutions for antibody-drug conjugate (ADC) drug discovery success in oncology, this book helps readers improve the drug safety and therapeutic efficacy of ADCs to kill targeted tumor cells. • Discusses the basics, drug delivery strategies, pharmacology and toxicology, and regulatory approval strategies • Covers the conduct and design of oncology clinical trials and the use of ADCs for tumor imaging • Includes case studies of ADCs in oncology drug development • Features contributions from highly-regarded experts on the frontlines of ADC research and development
Drug Repurposing In Cancer Therapy
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Author : Kenneth K.W. To
language : en
Publisher: Academic Press
Release Date : 2020-07-29
Drug Repurposing In Cancer Therapy written by Kenneth K.W. To and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-29 with Science categories.
Drug Repurposing in Cancer Therapy: Approaches and Applications provides comprehensive and updated information from experts in basic science research and clinical practice on how existing drugs can be repurposed for cancer treatment. The book summarizes successful stories that may assist researchers in the field to better design their studies for new repurposing projects. Sections discuss specific topics such as in silico prediction and high throughput screening of repurposed drugs, drug repurposing for overcoming chemoresistance and eradicating cancer stem cells, and clinical investigation on combination of repurposed drug and anticancer therapy. Cancer researchers, oncologists, pharmacologists and several members of biomedical field who are interested in learning more about the use of existing drugs for different purposes in cancer therapy will find this to be a valuable resource. - Presents a systematic and up-to-date collection of the research underpinning the various drug repurposing approaches for a quick, but in-depth understanding on current trends in drug repurposing research - Brings better understanding of the drug repurposing process in a holistic way, combining both basic and clinical sciences - Encompasses a collection of successful stories of drug repurposing for cancer therapy in different cancer types
Ai Pharma Artificial Intelligence In Drug Discovery And Development
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Author : Daniel D. Lee
language : en
Publisher: SkyCuration
Release Date : 2024-08-12
Ai Pharma Artificial Intelligence In Drug Discovery And Development written by Daniel D. Lee and has been published by SkyCuration this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-12 with Computers categories.
"AI Pharma: Artificial Intelligence in Drug Discovery and Development" is a comprehensive exploration of how artificial intelligence is reshaping the pharmaceutical industry. It reveals how machine learning, deep learning, and other advanced technologies are revolutionizing drug discovery and development. The book meticulously charts the evolution of AI's role, starting from the surge in data collection and processing to the latest breakthroughs in predictive modeling. It unveils AI's transformative impact on research and development, delving into how AI tools streamline target identification, molecule generation, and clinical trials, leading to faster, more accurate results. Key industry experts share insights on the challenges of navigating the vast amount of data produced, stressing the importance of data cleaning, curation, and ethical considerations in collection. Case studies highlight how startups and leading companies use AI algorithms for deep learning in drug development, identifying disease targets and generating new compounds with unprecedented precision. The book emphasizes practical applications, like predictive models for toxicity and safety in preclinical trials and patient recruitment optimization in clinical trials. Additionally, it tackles the intersection of AI with emerging technologies like the Internet of Medical Things (IoMT) and blockchain, showcasing how these complement AI in securing data and enhancing pharmaceutical supply chains. Readers will gain a deep understanding of the regulatory landscape, exploring FDA guidelines and global regulations that shape AI adoption. Interwoven throughout are the voices of thought leaders who address legal and ethical challenges, highlight the significance of partnerships, and stress the need for transparent and trustworthy AI models. They emphasize cross-disciplinary collaboration and tailored training strategies to cultivate AI talent that meets the growing needs of pharma. By examining the future of deep learning, computational research, and explainable AI, the book provides a strategic roadmap that researchers, policymakers, and developers can follow. Ultimately, this book is not only a roadmap but also a clarion call, urging stakeholders to build collaborative ecosystems that harness AI's potential for innovative pharmaceutical research and development. Through a rich, detailed narrative, readers are guided to understand the profound implications and exciting opportunities that await in this AI-driven pharmaceutical landscape
Artificial Intelligence And Machine Learning In Healthcare
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Author : Ankur Saxena
language : en
Publisher: Springer Nature
Release Date : 2021-05-06
Artificial Intelligence And Machine Learning In Healthcare written by Ankur Saxena and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-06 with Science categories.
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.
Deep Learning For The Life Sciences
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Author : Bharath Ramsundar
language : en
Publisher: O'Reilly Media
Release Date : 2019-04-10
Deep Learning For The Life Sciences written by Bharath Ramsundar and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-10 with Science categories.
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
Handbook Of Radiopharmaceuticals
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Author : Michael R. Kilbourn
language : de
Publisher: John Wiley & Sons
Release Date : 2021-04-12
Handbook Of Radiopharmaceuticals written by Michael R. Kilbourn and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-12 with Science categories.
Sorgfältig aktualisierte Neuauflage dieses wegweisenden Referenzwerk der radiopharmazeutischen Wissenschaften Die 2. Auflage des Handbook of Radiopharmaceuticals wirft einen umfassenden analytischen Blick auf das Fachgebiet und bietet aktuelle Informationen zu zentralen Themen, u. a. die Herstellung von Radionukliden, synthetische Methoden, Entwicklungen in der Radiopharmazie, Regelwerke, und zu einer Fülle praktischer Anwendungen. Als wertvolles Nachschlagewerk für Einsteiger und erfahrene Praktiker untersucht diese Publikation die neuesten Konzepte und Fragestellungen unter Berücksichtigung des gezielten Einsatzes diagnostischer und therapeutischer Radiopharmazeutika. Die Beiträge stammen von Experten verschiedenster Unterdisziplinen und lassen den Leser eintauchen in die Radiochemie, Nuklearmedizin, molekulare Bildgebung u.v.m. Die Nuklearmedizin und radiopharmazeutischen Wissenschaften haben sich seit Veröffentlichung der 1. Auflage stark verändert. Neue Radiopharmazeutika für Diagnostik und Therapie wurden von der FDA zugelassen, klinische PET- und SPECT-Scans haben drastisch zugenommen und Fortschritte im Bereich Künstliche Intelligenz haben zu signifikant verbesserten Forschungsverfahren geführt. Diese vollständig überarbeitete Auflage stellt den derzeitigen Erkenntnisstand des Fachgebiets vor, ergänzt um aktualisierte und neue Inhalte. Neue Kapitel beschäftigen sich mit heutigen Good Manufacturing Practice, regulatorischen Entwicklungen und neuen Ansätzen bei der Qualitätskontrolle. Damit wird sichergestellt, dass die Leserschaft über die aufregenden Entwicklungen der letzten Jahre rundum im Bilde ist. Dieses wichtige Referenzwerk - bietet durchgängig neue und überarbeitete Inhalte. - deckt zentrale Anwendungsbereiche in der Diagnostik und Therapie ab, für die Onkologie, Neurologie und Kardiologie. - unterstreicht die multidisziplinäre Ausrichtung der radiopharmazeutischen Wissenschaften. - zeigt, wie Pharmaunternehmen mit modernen Bildgebungsverfahren der Radiopharmazie neue Medikamente entwickeln. - untersucht heutige und neue Anwendungen der Positronen-Emissions-Tomographie (PET) und Single-Photonen-Emissions-Computertomographie (SPECT). Die Herausgeber sind anerkannte Experten der Fachrichtungen Radiochemie und PET-Bildgebung. Die 2. Auflage des Handbook of Radiopharmaceuticals: Radiochemistry and Applications ist ein Muss für Postdoktoranden, Forscher und Fachexperten in der Pharmazeutischen Industrie und richtet sich ebenso an die akademische Forschung und Lehre, an Graduierte und Einsteiger in das Fachgebiet der Radiopharmazeutika.