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.
This chapter presents various cloud platforms that are available in market offerings from different vendors. IBM provided a machine learning (ML) platform “IBM Watson Studio” (formerly “Data Science Experience”), and this is considered here for the field of study. An overview of artificial intelligence, ML, and deep learning (DL) with their relationship is deliberated. Discussion on popular DL architectures with elementary comparison is also considered.
Today information technologies have led to a vast number of innovations and developments in almost every field of advancement. In this context, recommender systems (RS) have been setting milestones in the service industry. If we look at the web-based services, it can be said that RS has contributed majorly to increase the reachability of products and to provide a sea of options for potential customers. This RS can also be used as a tool to support decision-making by the decision-makers. With this advancement of RS in the service industry, healthcare systems also do not lag. Health RS (HRS) are becoming an important platform for providing healthcare services, which would cut down the hectic schedule of visiting the doctors and waiting for hours to get checked. In the healthcare industry, RS already play a very significant role in terms of supporting decision-making process about any individual’s health. Keeping the very limited availability of resources in mind and the need for HRS to make its way into the chapter of milestones and innovations, it is important to introduce a set of knowledge and information for the researchers that are interested in HRS studies and can make huge advancements in this domain. Using HRS to suggest the most probable and appropriate medicines after taking into consideration the history of the individual can be a sub-domain to highly think about. Hence, this paper provides a literature study of the HRS domain in general which includes the literature, innovations, purpose, and methods of HRS, along with the new concept of HRS being used for medication purposes.