New Algorithm Developed to Predict Probable Virus Strains capable of Future Pandemics boosting Artificial Intelligence in Healthcare Market
Posted On March 22, 2021
Artificial Intelligence is emerging as a prominent technology to be inculcated in various sectors, making different industries more efficient. It has been seen to be incorporated in automobiles, entertainment, household appliances, etc. One of such industries is health care. Usage of artificial intelligence in this sector enables the doctor to provide good care for their patients while also detecting different diseases in a better and efficient manner.
Recently, a team of scientists has worked out a way to determine the next place where coronavirus can emerge by using Artificial Intelligence (AI). They used an amalgamation of machine learning and fundamental biology to develop an algorithm that has the ability to predict further potential hosts of the new virus strains that have been predicted till now. This can be considered a significant advancement of Artificial Intelligence in Healthcare market. It will help healthcare personnel to identify new viruses as they are recombining, providing us with essential time wherein we can be ready to fight against them or curb them while it is in the initial stages.
A new strain is generated through recombination of two existing coronaviruses; The two viruses infect the cell resulting in the production of a “daughter” virus, which is an entirely new strain. The team developed the algorithm by asking it to find such biological patterns that would predict which mammals are more susceptible to this virus. It revealed links between 411 strains of the virus and 876 mammals that might be able to contract Coronavirus. The most important part was to identify such species which can harbor several viruses at once.
The team was able to predict which of the species had a chance of getting affected by several coronaviruses. They are looked into species that were closely related to species that are known to carry the virus. Additionally, species sharing similar geographical space with typically affected species were also noted down. Through this, they concluded that many mammals had the potential to contract the virus than what previous screenings of animals had revealed.
Hence, several statistics were recalled, such as Greater horseshoe bat and Asian palm civet could be host to 32 and 68 various coronaviruses, respectively. Similarly, the algorithm predicted that in species like the dromedary camel, common hedgehog, and The European rabbit, Sars –CoV-2 might combine with other coronaviruses.
Researchers pointed that it is practically impossible to survey all the animals at all times, so their approach gives prioritization. They provide a list of species that should be kept on a “watch” so that viruses can be found while they are recombining. This would help target surveillance for new diseases and might lead to the prevention of upcoming pandemics.