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Artificial Intelligence in Microbial Research : Bridging the Gap / / edited by Babita Pandey, Devendra Pandey, Aditya Khamparia, Venkatesh Dutta, Valentina E. Balas
| Artificial Intelligence in Microbial Research : Bridging the Gap / / edited by Babita Pandey, Devendra Pandey, Aditya Khamparia, Venkatesh Dutta, Valentina E. Balas |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XVI, 450 p. 104 illus., 94 illus. in color.) |
| Disciplina | 579.1788 |
| Collana | Microorganisms for Sustainability |
| Soggetto topico |
Microbial populations
Microbiology Cytology Microbial ecology Artificial intelligence Machine learning Artificial intelligence - Data processing Microbial Communities Cellular Microbiology Environmental Microbiology Artificial Intelligence Machine Learning Data Science |
| ISBN | 981-9634-48-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Thematic Analysis of Media Influence on the Adoption of AI Climate Prediction Models in Microbial Agriculture Practices: A Case Study of Uttar Pradesh Using Diffusion of Innovations Theory -- Chapter 2. Understanding Media Influence on the Adoption of AI Climate Prediction Models in Microbiological Agricultural Practices: A Study of Uttarakhand -- Chapter 3. Advancements in Precision Agriculture: Integrating Machine Learning Techniques for Crop Monitoring and Management -- Chapter 4. Advances in Agricultural Analytics Machine Learning Applications for Crop Monitoring and Management -- Chapter 5. AI Driven Strategies for Microbial Infection from Discovery to Therapeutic Design -- Chapter 6. Use of Artificial Intelligence for Monitoring Algal Blooms in Aquatic Ecosystem -- Chapter 7. Ai-Yolact Model for Automatic Severity Grading Of Microbial Based Anthracnose Infection in Camellia Leaves -- Chapter 8. An Explainable AI Based CNN model for Plant Disease Diagnosis -- Chapter 9. Artificial Intelligent Enable Intelligent Bio-Sensor for Microbial Analysisfor Lung Health -- Chapter 10. Biosensors Guided Ai Interventions in Personalized Medicines -- Chapter 11. Education and Training for Developing Responsible AI Solutions in Healthcare -- Chapter 12. Automation of Drug Discovery & Development -- Chapter 13. Genome Studies and Disease Diagnosis -- Chapter 14. Exploring Explainable Artificial Intelligence in Healthcare: Issues, Challenges and Opportunities -- Chapter 15. Investigating Integron as the Principal Factor of Antibiotic Resistance in the Human Gut: A Holistic Perspective -- Chapter 16. Hybrid Deep Learning for Predictive Modelling of Microbial Biostimulants in Precision Agriculture -- Chapter 17. Challenges and Opportunities In Integrating Generative Al With Wearable Devices -- Chapter 18. Medical Image Analysis and Morphology Using Artificial Intelligence -- Chapter 19. Simulation of Biological Structures Using Generative Artificial Intelligence -- Chapter 20. Neuromuscular Disease Classification: Leveraging Deep Learning Feature Extractors and Applications. |
| Record Nr. | UNINA-9911007364703321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep Learning for Personalized Healthcare Services / / ed. by Vishal Jain, Hadi Hedayati, Salahddine Krit, Omer Deperlioglu, Jyotir Moy Chatterjee
| Deep Learning for Personalized Healthcare Services / / ed. by Vishal Jain, Hadi Hedayati, Salahddine Krit, Omer Deperlioglu, Jyotir Moy Chatterjee |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2021] |
| Descrizione fisica | 1 online resource (XVIII, 250 p.) |
| Collana | Intelligent Biomedical Data Analysis |
| Soggetto topico | COMPUTERS / Social Aspects / General |
| Soggetto genere / forma | Electronic books. |
| ISBN | 3-11-070812-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Preface -- Acknowledgments -- Contents -- Short Biography of Editors -- List of Contributors -- Deep learning for health and medicine -- Exploring Indian Yajna and mantra sciences for personalized health: pandemic threats and possible cures in twenty-first-century healthcare -- Advanced deep learning techniques and applications in healthcare services -- Visualizations of human bioelectricity with internal symptom captures: the Indo-Vedic concepts on Healthcare 4.0 -- Early cancer predictions using ensembles of machine learning and deep learning -- Deep learning in patient management and clinical decision making -- Patient health record system -- Prediction of multiclass cervical cancer using deep machine learning algorithms in healthcare services -- Comparative analysis for detecting skin cancer using SGD-based optimizer on a CNN versus DCNN architecture and ResNet-50 versus AlexNet on Adam optimizer -- Coronary heart disease analysis using two deep learning algorithms, CNN and RNN, and their sensitivity analyses -- An overview of the technological performance of deep learning in modern medicine -- Index |
| Record Nr. | UNINA-9910554282103321 |
| Berlin ; ; Boston : , : De Gruyter, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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