New genAI tool to detect bird flu virus exposure, boost H5N1 surveillance 

New Delhi, Aug 28 US researchers have developed a new and highly effective generative artificial intelligence (AI) tool to rapidly detect exposure to the H5N1 virus -- behind avian influenza or “bird flu”, and bolster national surveillance as the virus continues to spread in other animals.

The study, published in the journal Clinical Infectious Diseases, revealed that the AI tool quickly scans notes in electronic medical records and identifies high-risk patients who may have been infected with H5N1 bird flu.

“This study shows how generative AI can fill a critical gap in our public health infrastructure by detecting high-risk patients that would otherwise go unnoticed,” said corresponding author Katherine E. Goodman, Assistant Professor of Epidemiology and Public Health at the University of Maryland School of Medicine

“With H5N1 continuing to circulate in animals, our biggest danger nationwide is that we don’t know what we don’t know. Because we are not tracking how many symptomatic patients have potential bird flu exposures, and how many of those patients are being tested, infections could be going undetected. It’s vital for healthcare systems to monitor for potential human exposure and to act quickly on that information,” Goodman added.

Further, the AI tool requires only 26 minutes and costs just 3 cents per patient, said the team, citing the potential of the method "to create a national network of clinical sentinel sites for emerging infectious disease surveillance" to better monitor emerging epidemics.

Using a generative AI large language model, the research team analysed 13,494 visits in hospital emergency departments from adult patients in urban, suburban, and rural areas in 2024.

These patients all had acute respiratory illness (such as cough, fever, congestion) or conjunctivitis -- symptoms consistent with early H5N1 infections. The goal was to assess how well generative AI could find high-risk patients who may have been overlooked at the time of initial treatment.

Scanning all of the emergency department notes, the model flagged 76 because they mentioned a high-risk exposure for bird flu, such as working as a butcher or at a farm with livestock, like chickens or cows.

After a brief review by research staff, 14 patients were confirmed to have had recent, relevant exposure to animals known to carry H5N1, including poultry, wild birds, and livestock.

These patients were not tested specifically for H5N1, so their potential bird-flu infections were not confirmed, but the model worked to find those “needle in a haystack” cases among thousands of patients treated for seasonal flu and other routine respiratory illnesses.

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