Using Nigerian patient data, we developed an algorithm that learns from the patient data, identifies patterns, and makes intelligent decisions to provide alerts and detection of a patient's HBV infection status. The aim is to enhance clinical decision-making and improve patient outcomes. Enabling earlier care should give millions of people a better quality of life and help reduce HBV prevalence.
We used the results of normal blood tests that measure red and white blood cells, salts, enzymes and other blood chemicals, along with results of tests for hepatitis B. Routine blood tests can be very useful in facilitating early diagnosis if the subtle interactions between measurements can be spotted. Patterns of interactions may be a signal of disease. But it's easy to miss them.
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