1. A review of bone tissue engineering for the application of artificial intelligence in cellular adhesion prediction
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María de Lourdes Sánchez
Abstract
Artificial intelligence (AI) is changing, at a fast pace, all aspects of science, technology, and society in general, giving rise to what is known as the 4th Industrial Revolution. In this chapter, we review the literature regarding AI applications to bone tissue engineering, and more particularly, to cell adhesion in bone scaffolds. The works found are very few (only six works), and we classify them according to the AI technique used. The question we want to address in this chapter is what AI techniques were used and what exactly have they been used for. The chapter shows that the most used AI tools were the artificial neural network, in their different types, followed by cellular automata and multiagent systems. The intended use varies, but it is mainly related to understanding the variables involved and adjusting a model that provides insight and allows for a better and more informed design process of the scaffold.
Abstract
Artificial intelligence (AI) is changing, at a fast pace, all aspects of science, technology, and society in general, giving rise to what is known as the 4th Industrial Revolution. In this chapter, we review the literature regarding AI applications to bone tissue engineering, and more particularly, to cell adhesion in bone scaffolds. The works found are very few (only six works), and we classify them according to the AI technique used. The question we want to address in this chapter is what AI techniques were used and what exactly have they been used for. The chapter shows that the most used AI tools were the artificial neural network, in their different types, followed by cellular automata and multiagent systems. The intended use varies, but it is mainly related to understanding the variables involved and adjusting a model that provides insight and allows for a better and more informed design process of the scaffold.
Kapitel in diesem Buch
- Frontmatter I
- Preface VII
- Contents XI
- List of contributors XIII
- 1. A review of bone tissue engineering for the application of artificial intelligence in cellular adhesion prediction 1
- 2. Implementation and classification of machine learning algorithms in healthcare informatics: approaches, challenges, and future scope 21
- 3. Cardiac arrhythmia recognition using Stockwell transform and ABC-optimized twin SVM 35
- 4. Computational intelligence approach to address the language barrier in healthcare 53
- 5. Recent advancement of machine learning and deep learning in the field of healthcare system 77
- 6. Predicting psychological disorders using machine learning 99
- 7. Automatic analysis of cardiovascular diseases using EMD and support vector machines 131
- 8. Machine learning approach for exploring computational intelligence 153
- 9. Classification of various image fusion algorithms and their performance evaluation metrics 179
- 10. Recommender system in healthcare: an overview 199
- 11. Dense CNN approach for medical diagnosis 217
- 12. Impact of sentiment analysis tools to improve patients’ life in critical diseases 239
- 13. A fuzzy entropy-based multilevel image thresholding using neural network optimization algorithm 253
- 14. Machine learning in healthcare 277
- 15. Computational health informatics using evolutionary-based feature selection 309
- Index 329
Kapitel in diesem Buch
- Frontmatter I
- Preface VII
- Contents XI
- List of contributors XIII
- 1. A review of bone tissue engineering for the application of artificial intelligence in cellular adhesion prediction 1
- 2. Implementation and classification of machine learning algorithms in healthcare informatics: approaches, challenges, and future scope 21
- 3. Cardiac arrhythmia recognition using Stockwell transform and ABC-optimized twin SVM 35
- 4. Computational intelligence approach to address the language barrier in healthcare 53
- 5. Recent advancement of machine learning and deep learning in the field of healthcare system 77
- 6. Predicting psychological disorders using machine learning 99
- 7. Automatic analysis of cardiovascular diseases using EMD and support vector machines 131
- 8. Machine learning approach for exploring computational intelligence 153
- 9. Classification of various image fusion algorithms and their performance evaluation metrics 179
- 10. Recommender system in healthcare: an overview 199
- 11. Dense CNN approach for medical diagnosis 217
- 12. Impact of sentiment analysis tools to improve patients’ life in critical diseases 239
- 13. A fuzzy entropy-based multilevel image thresholding using neural network optimization algorithm 253
- 14. Machine learning in healthcare 277
- 15. Computational health informatics using evolutionary-based feature selection 309
- Index 329
