Machine Learning Tool Detects Hepatitis B Early, Saving Lives

More than 296 million people worldwide live with hepatitis B, a potentially life-threatening liver infection caused by the hepatitis B virus (HBV). Most don't know they are infected, so they don't get medical care. Clinical care improves the patient's outcome and can prevent them from infecting others, reports Busayo I. Ajuwon and Brett A. Lidbury for The Conversation.

A group of researchers from the Australian National University conducted a study on machine learning and infectious diseases, particularly focusing on hepatitis B (HBV) in Nigeria. They discovered a high prevalence of HBV in the country, with a rate of 9.5% (considered high if above 8%), which varied across different geopolitical zones.

The lack of affordable testing is posing a challenge in Nigeria and to address this issue, researchers developed a tool utilizing machine learning algorithms. By analyzing Nigerian patient data, the algorithm learned from patterns, making intelligent decisions to provide alerts and detecting a patient's HBV infection status. The primary goal is to improve clinical decision-making and enhance patient outcomes.

Earlier detection and care for HBV infections, could significantly enhance the quality of life for millions of people in Nigeria and by facilitating earlier interventions, researchers hope to contribute to reducing the overall prevalence of HBV in the country.

This article originally appeared on The Conversation.

Image via Roche.