Technical field of invention:

The present invention relates implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine.

Prior Art:

Covid-19 is a highly contagious disease that is caused by severe acetate respiratory syndrome coronavirus 2 (SARS-COV-2). The disease has spread worldwide leading to a pandemic situation. Several testing methods and precautions have been taken to break the chain of corona virus disease. The impact the disease has on world population cannot be imagined. The disease not just spoiled the health but also took the financial and economic status to drip to the lowest point. Vaccination has been introduced to avoid the affect of covid19 and to boost immunity.

Covid 19 vaccine is a vaccine intended to provide acquired immunity against corona virus that causes corona virus disease. Existing vaccines are administrated in either two doses or single dose. Vaccine platform in development may improve flexibility for antigen manipulation, and effectiveness for targeting mechanisms of covid 19 infection in suspectable population subgroups such as healthcare workers, the elderly, children, pregnant women and people with weakened immune system. But the exact point is that the existing vaccines results are yet to be analysed to prove their immunity boosting level.

A number of different types of analysis of vaccinated and non-vaccinated are known in the prior art. For example, the following patents are provided for their supportive teachings and are all incorporated by reference.

Coronavirus (covid-19) vaccines for developing countries: an equal shot at recovery

As the roll out of coronavirus (COVID-19) vaccines begins, this policy brief asks how to ensure vaccines for all. In doing so, it examines the case for multilateral approaches to access and delivery, maps key challenges, and identifies priority actions for policy makers. The absence of a comprehensive approach to ensure vaccine access in developing countries threatens to prolong the pandemic, escalating inequalities and delaying the global economic recovery. While new collaborative efforts such as ACT Accelerator and its COVAX initiative are helping to bridge current gaps, these are not enough in circumstances where demand far outstrips supply. Based on the current trajectory, mass immunization efforts for poorer countries could be delayed until 2024 or beyond, prolonging human and economic suffering for all countries. Policy actions to support equitable vaccine access in developing countries include: (i) supporting multilateral frameworks for equitable allocation of vaccines and for crisis response, resilience and prevention; (ii) highlighting the role of development finance; and, (iii) promoting context-driven solutions.

The proposed invention aims implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine. The databases of health parameters of both vaccinated and non-vaccinated population are clustered and classified to know the level of immunity levels of both the groups so that we can say that vaccination can fight against variants of corona virus. The results are stored and displayed over cloud in the form of graphs and bar charts.

Above information is presented as background information only to assist with an understanding of the present disclosure. No determination has been made, no assertion is made, and as to whether any of the above might be applicable as prior art with regard to the present invention.

In the view of the foregoing disadvantages inherent in the known types of Machine learning approaches now present in the prior art, the present invention provides an improved system. As such, the general purpose of the present invention, which will be described subsequently in greater detail, is to provide a new and improved smart system to study the impact of vaccination the immune system that has all the advantages of the prior art and none of the disadvantages.

Objective of the invention

The primary object of the present invention is implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine.

Summary of the invention:

Accordingly following invention is implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine.

According to an embodiment, Covid 19 vaccine is a vaccine intended to provide acquired immunity against corona virus that causes corona virus disease. There is a need for a system that will analyse the impact of vaccination and compare them with non-vaccinated population. The proposed invention is implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine to arrive at conclusions.

Detailed description of invention:

The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.

In any embodiment described herein, the open-ended terms "comprising," "comprises,” and the like (which are synonymous with "including," "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like.

The present invention is implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine. Covid 19 which is highly contagious disease, a pandemic that has hit the world has taken a troll on global economy as well as life style of the population of the world. Not just a kind of virus but variants are emerging with much stronger structures which is very difficult for the people to cope up with and lead their normal life. Thus, the option that was provided from health care professionals is getting vaccinated. But still there are very less studies to analyse the level of impact the vaccination has on the immunity levels.

There is a need for a system that will analyse the impact of vaccination and compare them with non-vaccinated population. The proposed invention is implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine to arrive at conclusions. The immunity levels of vaccinated and non-vaccinated population.

Reference will now be made in detail to the exemplary embodiment of the present disclosure. Before describing the detailed embodiments that are in accordance with the present disclosure, it should be observed that the embodiment resides primarily in combinations arrangement of the system according to an embodiment herein and as exemplified in FIG. 1

The data related to a particular region is collected and divided on vaccinated group as well as non-vaccinated group. The vaccinated people’s info is stored on database and nonvaccinated database is stored on database. The health parameters of vaccinated and non-vaccinated people are stored on database and respectively. The machine learning unit clusters and classifies the data sets form both the database and and wants to analyse the factors that has boosted immunity power in vaccinated group. The results are displayed on mobile phone or any electric gadget over the cloud.

Figure 1 illustrates the flow diagram of implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine. The population is selected and divided into vaccinated and non-vaccinated group and those data are stored on database and respectively. The database of vaccinated group contains data set regarding the health parameters and the health parameters of non-vaccinated group are stored on database. The parameters are analysed to get evidence that it improves immunity and results are displayed in display unit over cloud. The machine learning unit clusters and classifies data sets form database.

In the following description, for the purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of the arrangement of the system according to an embodiment herein. It will be apparent, however, to one skilled in the art that the present embodiment can be practiced without these specific details. In other instances, structures are shown in block diagram form only in order to avoid obscuring the present invention.

Additional advantages and modification will readily occur to those skilled in art. Therefore, the invention in its broader aspect is not limited to specific details and representative embodiments shown and described herein. Accordingly various modifications may be made without departing from the spirit or scope of the general invention concept as defined by the appended claims and their equivalents.

While the invention has been described and illustrated with reference to certain particular embodiments thereof, those skilled in the art will appreciate that various adaptations, changes, modifications, substitutions, deletions, or additions of procedures and protocols may be made without departing from the spirit and scope of the invention.

Claims:

1. This invention analyzes implementing machine learning approach for determining and comparing the immunity levels of vaccinated and unvaccinated people with covid-19 vaccine. ,