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Full Description
The book emphasizes the technological advancements in tissue engineering related to biomaterials and biomanufacturing techniques. It further discusses important topics such as 3D bioprinting, process parameter optimization, Convolutional Neural Network (CNN) for stem cell imaging, diabetes risk prediction and Parkinson's disease detection using machine learning, telehealth systems, acute pancreatitis, and data-driven monitoring of chronic diseases.
This book:
Explores the role of artificial intelligence in designing biomaterials, optimizing fabrication processes, and predicting tissue formation
Focuses on technological advancements in tissue engineering related to biomanufacturing techniques, and biomaterials
Discusses the denture base acrylic resins, brain tumor detection, CNN for stem cell imaging and machine learning for diabetes risk prediction and Parkinson's disease detection.
Covers acute myocardial infarction, post-operative urinary retention, telehealth systems, graph convolutional network, and acute pancreatitis.
Explains the role of serum magnesium levels in febrile convulsions and Apache-II Score and Ranson Criteria with Modified CT Severity Index.
It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of manufacturing engineering, biomedical engineering, materials science, biomaterials, mechanical engineering, and production engineering.
Contents
1. Recent Technological Developments in Tissue Engineering. 2. The Future of Tissue Engineering: Integrating Machine Learning, AI, and Computer Vision. 3. 3D Bioprinting Techniques for Tissue Engineering Applications. 4. Natural Biomaterials for Tissue Engineering and Regenerative Medicine. 5. Advanced Synthetic Biomaterials for Tissue Engineering and Regenerative Medicine. 6. Study to Analyze the Efficacy of Three Types of Polishing Techniques on Two Commercially Available Denture Base Acrylic Resins. 7. Detecting the Accuracy of Cancer Stem Cell in Brain Tumor. 8. User Enabled Brain Tumor Detection. 9. CNN for Stem Cell Imaging: Existing Constraints and Future Perspectives in Artificial Intelligence. 10. Evaluation of Focal Solid Hepatic Lesions Using Shear Wave Elastography. 11. Diabetes Risk Prediction System using Machine Learning. 12. Evaluation of Coronary Artery Disease Risk Factors Among Patients with And Without Non-Alcoholic Fatty Liver Disease. 13. Study of Relation of Blood Sugar Level with Outcome in Acute Myocardial Infarction (Stemi and Nstemi) in Non-Diabetic Patients. 14. Detection of Parkinson's Disease Using Machine Learning. 15. Preventing Post-Operative Urinary Retention in Elderly Males Undergoing Elective Surgery. 16. Substantiating Random Forest Algorithm For Prognosis of Various Infirmities. 17. Assessing the Perception of Customers Towards Telehealth Systems & Intention To Adopt with Reference To Uttar Pradesh. 18. The Quest for Novel Drugs against COVID-19 - In-Silico Study. 19. Graph Convolutional Network for COVID-19 Detection from X ray: Advancing Accurate Diagnosis. 20. A Case-Control Study on the Role of Serum Magnesium Levels in Febrile Convulsions. 21. Apache-II Score and Ranson Criteria with Modified CT Severity Index in Predicting the Severity of Acute Pancreatitis: A Comparative Study. 22. Comparative Study Between SpotUrine Protein to Creatinine RatioAnd 24-Hour Urine Protein In TypeTwo Diabetic Patients With Nephropathy. 23. The Role of Electrocardiogram in Localising Culprit Vessel Occlusion in St-Segment Elevation Myocardial Infarction. 24. Correlation Of Early Post-Cataract Surgery Related Oct Changes with Its Intra-Operative Surgical Complications.
