Contents

Chapters in this book

1. Frontmatter I
2. Dedication V
3. Preface VII
4. Contents IX
5. 1 Understanding artificial intelligence: an introduction, history, and foundations 1
6. 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 25
7. 3 Cellular image classification and identification of genetic variations using artificial intelligence 47
8. 4 Artificial intelligence in bacterial staining and cell counting 65
9. 5 Use of artificial intelligence in the prediction of microbial species 79
10. 6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions 97
11. 7 AI in food production and processing: applications and challenges 125
12. 8 Artificial intelligence in microbial food safety 153
13. 9 AI in plant growth promotion and plant disease management 183
14. 10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology 207
15. 11 Artificial intelligence in diagnostics 229
16. 12 Artificial intelligence in bacterial culture plate images 263
17. 13 Prediction of antimicrobial activity using artificial intelligence 281
18. 14 Artificial intelligence and MALDI-TOF MS 313
19. 15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare 337
20. 16 Reimagining perfusion bioreactors with artificial intelligence 357
21. Index 381