Nigerian Institute of Medical Research

• More than 296 million people worldwide live with hepatitis B, a potentially life-threatening liver infection caused by the hepatitis B virus (HBV).
• Early detection of HBV-infected patients could therefore improve patient prognosis and stop transmission within populations.
• We are among a group of researchers at the Australian National University who study machine learning and infectious disease.
• Enabling earlier care should give millions of people a better quality of life and help reduce HBV prevalence.

How did we do the work?

• The institute is Nigeria’s foremost medical research institute and it hosts a dedicated hepatitis B clinic.
• Routine blood tests can be very useful in facilitating early diagnosis if the subtle interactions between measurements can be spotted.
• One reason machine learning is so powerful is that it does not require humans to tell the computer which features to identify.

What did we find?

• We then translated this into a user-friendly, web-accessible app to use in further studies.
• The tool found that a combination of two enzymes, patient age and white blood cell count was the strongest predictor of HBV infection.
• Serum albumin, a liver function marker, was also identified as an important predictive marker of infection.

What’s next?

• Before a tool like this is put to work in routine clinical practice, it needs to be validated using diverse data.
• Our machine learning tool was trained with data from Nigeria, so its performance may be limited to that setting.
• We are in the process of training our algorithm with more data from other sources and validating its robustness in other settings.