Predictive Analytics for Toxicology
Applications in Discovery Science
- 252 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
Predictive data science is already in use in many fields, but its application in toxicology is new and sought after by non-animal alternative testing initiatives. Predictive Analytics for Toxicology: Applications in Discovery Science provides a comprehensive overview of the application of predictive analytics in the field of toxicology, highlighting its role and applications in discovery science.
This book addresses the challenges of accurately predicting high-level endpoints of toxicity and explores the use of computational and artificial intelligence research to automate predictive toxicology. It underscores the importance of predictive toxicology in proposing and explaining adverse outcomes resulting from human exposures to specific toxicants, especially when experimental and observational data on the toxicant are incomplete or unavailable.
Key features:
- Includes a plain language description of predictive analytics in toxicology adding an overview of the wide range of applications
- Examines the science of prediction, computational models as an automated science and comprehensive discussions on concepts of machine learning
- Opens the hood on AI and its applications in toxicology
- Features coverage on how in silico toxicity predictions are translational science tools
The book integrates strategies and practices of predictive toxicology and offers practical information that students and professionals of the toxicology, chemical, and pharmaceutical industries will find essential. It fulfills the expectations of student researchers seeking to learn predictive analytics in toxicology. This book will energize scientists to conduct predictive toxicology modeling using artificial intelligence and machine learning, and inspire students and seasoned scientists interested in automated science to pick up new research using predictive in silico models to evaluate chemical-induced toxicity.
With its focus on practical applications and real-world examples, this book serves as a guide for navigating the complex issues and practices of discovery toxicology. It is an essential resource for those interested in computer-based methods in toxicology, providing valuable insights into the use of predictive analytics.
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Information
Table of contents
- Cover
- Half-Title Page
- Title Page
- Copyright Page
- Dedication
- Table of Contents
- About the Author
- Preface
- 1 Finding No Limit: Discovery Science
- 2 Exploring the Science of Prediction
- 3 Predictive Analytic Approaches
- 4 The Role of Predictive Analytics in Translational Science
- 5 Toxicology and Artificial Intelligence
- 6 The Explosion of Computational Approaches for Hazard Identification
- 7 Opportunities for Computational Modeling in Toxicology Prediction
- 8 Key Challenges in Computational Methods
- 9 Predictive Analytics in Driving Growth in Toxicology
- Index