Home Healthcare AI Helps in Identifying Patients who are Highly Susceptible to Cholera Infection

AI Helps in Identifying Patients who are Highly Susceptible to Cholera Infection

AI Helps in Identifying Patients who are Highly Susceptible to Cholera Infection
Images: Flickr Unsplash Pixabay Wiki & Others

Emerging technologies like artificial intelligence and machine learning are continuously proving to be highly useful in carrying out various things. In healthcare, for instance, scientists recently created machine-learning algorithms that can be used to recognize patterns in the bacteria found in a patient’s gut to assess the likelihood of cholera infection.

Thanks to the recent findings, the researchers are convinced that artificial intelligence could play a vital role in areas highly prone to cholera infections. The reason for this is because the technology can be utilized in analyzing trillions of bacteria, which surpasses the ability of humans to do so by far. Even so, the remarkable study displays the ability of machine learning to unearth medical insights that would have remained undiscovered.

The research involves a partnership between the Bangladesh-based International Center for Diarrheal Disease Research, Duke University, and the Massachusetts General Hospital. The research matters a lot since scientists are yet to discover the reason why some people when exposed to cholera get infected while others do not.

MORE – Top 10 Ways Artificial Intelligence is Impacting Healthcare

MORE – RPA – 10 Powerful Examples in Enterprise

Over the years, Bangladesh has experienced high cases of cholera outbreaks and the International Center for Diarrheal Disease Research has been at the forefront in efforts to test, as well as disseminate vaccines and treatments for the disease in the area.

To conduct this study, researchers spotted Bangladeshi 76 households whereby one of the residents had been hospitalized for cholera infection, which put the other members of the area at risk of infection. The researchers obtained rectal swabs from the participants of the exercise and then tracked them to identify whether they later developed cholera.

Based on the study’s findings nearly a third of all the patients got infected with cholera while the rest did not. Through the data gathered, the machine learning algorithm developed by the researchers recognized almost 1000 bacterial taxa, which appeared to indicate whether a given patient would be infected with the disease.

According to Regina C LaRocque, assistant professor of medicine at Harvard Medical School and senior author, the study identified that this predictive microbiota was as good at forecasting who gets infected with cholera as the risk factors that the world has known for decades. She added that the team of researchers involved in the study had managed to discover an entirely new component of cholera risk that was not known about previously. Furthermore, Lawrence A. David, a molecular genetics and microbiology assistant professor at Duke School of Medicine, asserted that the information could assist researchers in preventing cholera infections.

Lawrence also told Healthcare Analytics News that some of the preventative techniques that the researchers foresee including recognizing types of microbiota that are related to susceptibility as well as examining interventions known for discouraging the risk-related microbiota. For him, sanitation and nutrition are some examples of interventions that can benefit the microbiome.

According to WHO, lack of clean water and poor sanitation make up some of the major risk factors that cause cholera, which is known to infect between 1.3 and 4 million individuals annually.

Lawrence said that the revolutionary technology could come in handy in understanding other diseases. Additionally, the study was published in last month’s Journal of Infectious Diseases and is dubbed Human Gut Microbiota Predicts Susceptibility to Vibrio Cholerae Infection.

Source HCANews