In our research in classifying the real-world images by application and functionality, we use the topological data analysis (TDA) framework. There are many uses in a variety of fields (medical/biological, social, engineering, etc.) to detect boundaries, clusters, abnormal regions in images and other data [ 5 ].
A full-scale social business reform is needed. For a start, the World Health Organization needs to audit the global health system and make recommendations on how to improve it for the future. Its report on Covid-19 has, thankfully, been timely. And going forward, the WHO must increasingly focus on the human-rights implications of the system that makes life precarious for millions, everywhere in the world; and it needs to be democratic as well as accountable.
Coronavirus has exposed how global economic and social systems are unable to deliver the right health outcomes for the most vulnerable people across the world. We need social business changes to fix this.
Chapter Summary/Discussion/Conclusions: In this chapter, we presented how Machine Learning and statistical techniques are used to solve a particular problem as well as how they can be applied to other problems, how to understand the statistics used in ML techniques, how to model the world, and how we can effectively extract insights from data.
There was a lot of work done in Australia, Switzerland, and the Netherlands. This was mostly about modeling, given that the UK was in a lockdown, and was trying to figure out what they can actually do. They had no testing capability. We had some statistical analysis of the data.