Abstract- Artificial Intelligence engineers in order to study the parameters effecting how harmful or non-harmful a variant of virus is using tools in AI require data of genomic structure of both the vaccine and of the virus variant. The aim is to predict the graph, spread, location and severity of a virus using Artificial Intelligence. The genomic structure of the virus, the genomic structure of the vaccine shall be needed to be given as input to Artificial Intelligence to get insight on it. Further, under what conditions mutations happened and this can help AI predict where and how to stop the virus. Also, which human genes are most effected by a particular category of virus can also be investigated once the study starts.
This is a short article, out of the news that a new corona variant called Omicron have come up, first found in South Africa. Now, this is yet another variant of corona. We may or may not be yet able to stop mutations, but as far as I know this virus variant have a lot many changes in structure. The structure plays a key role in various things. This article emphasises how Artificial Intelligence can help in predicting the severity of virus, it is not yet experimentally proved to be correct, but as a science progresses this needs to be studies, just like cancer can be predicted accurately based on genetic information, same we may be able to get some insight. Though at this stage we cannot guarantee what, but this is how various kinds of cancers such as colon, leukemia use Artificial Intelligence to predict certain concerns.
So, my viewpoint is — we must be able to study the following parameters in understanding how harmful or non-harmful a variant of virus is using Artificial Intelligence. The aim is to predict the graph and severity of a virus using Artificial Intelligence tools. The following can be taken as input by the data scientists who are willing to work on this topic. The parameters to be inputted to the neural model are:
- The structure of mutant of virus, or may be any virus. And the genomic sequence of the specific variant of the virus.
- The location,
- The temperature of the place,
- The humidity of the place,
- The evaporation rate of the place,
- The atmospheric pressure at that time
- Weather condition- good, bad, worse.
- Month of the year
- Average weight of people in locality effected…and so on.
- Gene data of people in the region where data was collected
- How much the virus is different from previous virus on which neural model was learned
Now, all this is motivated by the fact that even cancer of types such as leukemia and colon cancer can be detected by artificial intelligence to a very high accuracy now a days with gene data. So, the question is how to study the co-relation of these things. All these studies shall be useful to know the impact of a virus on a particular person, living in a particular place at a specific time and in presence of certain specific genetic information of virus. This shall let us know does virus effects a particular gene more, is so measures to safeguard that gene shall be researched more. More is needed to know which genes makes a virus more transmissible. Does certain temperature or atmospheric conditions or month lays more virus spread. This can also help people plan travel well in advance based on availability of such predictions, which shall be a good help to people in a lot of ways. But till the time the science behind the virus spread and logics are understood with help of genomic sequence as is studied for cancer detection, one cannot say anything for certain. It may help in some way.