Due to their high predictive and informative potential, machine learning and deep learning have emerged as essential tools to advance microbiome research. This book provides insights and research findings related to AI in microbiology and demonstrates how AI can be applied to solve complex problems, accelerate research, and improve our understanding of microorganisms. It covers AI and machine learning techniques in plant growth and plant protection, in clinical, food and environmental microbiology. AI in microbiology is an interdisciplinary field, and this book will help bridge the gap between computer science, data analytics, and microbiology.

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Yes, you can access Artificial Intelligence in Microbiology by Pankaj Kumar,Vivekanand Vivekanand,Nidhi Pareek,Ramesh Chandra Dubey in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Year

eBook ISBN

Topic

Subtopic

Artificial Intelligence (AI) & Semantics

Index

Biological Sciences

Title Page
Copyright
Contents
Frontmatter
Dedication
Contents
1 Understanding artificial intelligence: an introduction, history, and foundations
2 Basics of machine learning (ML) and deep learning (DL), secondary data source and training, application and AI tools, challenges, and future perspectives of AI
3 Cellular image classification and identification of genetic variations using artificial intelligence
4 Artificial intelligence in bacterial staining and cell counting
5 Use of artificial intelligence in the prediction of microbial species
6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions
7 AI in food production and processing: applications and challenges
8 Artificial intelligence in microbial food safety
9 AI in plant growth promotion and plant disease management
10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology
11 Artificial intelligence in diagnostics
12 Artificial intelligence in bacterial culture plate images
13 Prediction of antimicrobial activity using artificial intelligence
14 Artificial intelligence and MALDI-TOF MS
15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare
16 Reimagining perfusion bioreactors with artificial intelligence
Index
Index

About this book

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Table of contents