
To sort through thousands of different species of microbe living in the intestines of people exposed to cholera, a Duke team used artificial intelligence and machine learning to look for patterns. These patterns could indicate who among the approximately one billion people around the globe at risk of cholera infection will get sick with the diarrheal disease.
"These are patterns that even the most sophisticated scientist couldn't detect by eye," said Lawrence A. David, Ph.D., a senior author of the study and assistant professor of molecular genetics and microbiology at Duke School of Medicine. "While some people are warning about artificial intelligence leading to killer robots, we are showing the positive impact of AI in its potential to overcome disease."
The research, published this week in the Journal of Infectious Diseases, suggests that a focus on gut microbes may be important for developing improved vaccines and preventive approaches for cholera and other infectious diseases.
"Our study found that this 'predictive microbiota' is as good at predicting who gets ill with cholera as the clinical risk factors that we've known about for decades," said Regina C. LaRocque, M.D., MPH, of the Massachusetts General Hospital Division of Infectious Diseases, a senior author of the study and assistant professor of medicine at Harvard Medical School. "We've essentially identified a whole new component of cholera risk that we did not know about before." Cholera can spread rapidly in areas with unsafe drinking water and inadequate sanitation, causing millions of cases of acute watery diarrhea every year. Despite its global impact, scientists still do not completely understand why some people who come into contact with the cholera bacterium become sick while others do not. Some studies have pinpointed a few risk factors, such as age, blood type and previous infections, but these only partially explain the differences in clinical outcomes after exposure to the pathogen.
The team showed that the model generated by artificial intelligence could predict illness even better than models previously built by infectious disease experts. The model also suggested hypotheses that might explain why the patterns identified by the computer are associated with disease. For example, when the researchers picked a bacterial species identified by their model and studied it in the laboratory, they found that the bacteria promoted the growth of cholera in test tubes. Their findings indicate that the composition of the gut microbiota could create an environment that is more or less hospitable to pathogens. "Scientists have long had a hunch that gut bacteria might affect a person's susceptibility to diarrheal diseases, but our study is among the first to show this in a real-world setting," LaRocque said.
Source: Eurekalert
Advertisement
|
Recommended Readings
Latest News on IT in Healthcare




