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Artificial Intelligence and Biological Sciences
About this book
Advancements of AI in medical and biological sciences have opened new ways for drug development. Novel therapeutic molecules and their target action can be easily predicted and can be modified. AI helps in disease detection and diagnosis faster. The breakthrough of AI is made especially in the area of personalized precision medicine, host-pathogen interaction and predictive epidemiology. These approaches could help in faster decision-making with minimal errors that can improve risk analysis, especially disease diagnosis and selecting treatment strategy. In agricultural practices, an exact combination of fertilizers, pesticides, herbicides, soil management, water requirement analysis, yield prediction and overall crop management can be modified by implementing AI interventions. AI could provide a better improvement in agriculture, medical research, pharmaceuticals and bio-based industries for a sustainable life.
The key features of this book are: AI in medical Sciences, biotechnology and drug discovery; Application of AI in Digital Pathology, cytology and bioinformatics; Overview of AI, Machine Learning and Deep Learning; Impact of Artificial Intelligence in Society; Artificial Intelligence in Pharmacovigilance; and Ethics in Artificial Intelligence. The volume aims to comprehensively cover the application of AI in biological sciences. It is a collection of contributions from different authors who have several years of experience in their specific areas. The book will be useful for pharma companies, CROs, product developers, students, researchers, academicians, policymakers and practitioners.
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Preface
- Contents
- List of Contributors
- Chapter 1 Overview of Artificial Intelligence
- Chapter 2 Evolution of Artificial Intelligence
- Chapter 3 Futuristic Application of Artificial Intelligence
- Chapter 4 Comparison of Human Intelligence with Artificial Intelligence
- Chapter 5 Advantages and Disadvantages of Artificial Intelligence
- Chapter 6 Comparison of Machine Learning and Deep Learning
- Chapter 7 Supervised Learning
- Chapter 8 Unsupervised Learning
- Chapter 9 Ethics in Artificial Intelligence
- Chapter 10 Learning Anatomy using Virtual Dissections: Previous Experience and Future Directions Integrating Artificial Intelligence and Multiple Approaches
- Chapter 11 Artificial Intelligence in Medical Sciences
- Chapter 12 Artificial Intelligence in Biotechnology
- Chapter 13 Artificial Intelligence in drug Discovery
- Chapter 14 Artificial Intelligence in Biosciences
- 15 Artificial Intelligence in System Biology
- 16 Artificial Intelligence-based Methods for Drug Screening
- 17 Artificial Intelligence in Synthetic Biology
- Chapter 18 Cognitive Artificial Intelligence
- Chapter 19 Artificial Intelligence in Digital Biology
- Chapter 20 Artificial Intelligence in Biological Data Science
- Chapter 21 Artificial Intelligence in Bioinformatics
- Chapter 22 Impact of Artificial Intelligence on Society: A Healthcare Perceptive
- Chapter 23 Application of AI in Digital Pathology
- Chapter 24 Deep Learning and AI in Digital Cytology
- Chapter 25 Applications of Artificial Intelligence in RNA-sequencing
- Chapter 26 Artificial Intelligence in Pharmacovigilance and Materiovigilance
- Chapter 27 AI in Imaging: Emphasis on Medical Imaging
- Chapter 28 The Decisive Role of Artificial Intelligence in Toxicology: Advancements and Applications
- Index
- About the Editor