More than 296 million people worldwide are affected by hepatitis B, which is caused by the hepatitis B virus (HBV). However, most people do not know they have this potentially life-threatening liver infection and miss out on medical care. Improving clinical care can help patients recover and prevent further infections.
In Nigeria, researchers from the Australian National University conducted a study on machine learning and infectious diseases, with a particular focus on HBV. The research showed that the rate of HBV in Nigeria was significantly high, with a prevalence rate of 9.5%.
One of the main challenges is to provide affordable testing to people in Nigeria. In response to this issue, the researchers developed a machine learning algorithm to help classify Nigerian patients with HBV infection status. By learning from patterns in the patient data, the algorithm is able to make intelligent decisions and provide alerts to medical professionals. The primary goal is to help improve clinical decision-making and ultimately, enhance patient outcomes.
Earlier detection and treatment of HBV infections can have a significant impact on patients’ quality of life in Nigeria. If diagnosed earlier, patients are more likely to receive the appropriate care and support they need. Medical interventions could also help reduce the overall prevalence of HBV in the country.
The machine learning tool developed by the researchers in Nigeria has broadened access to affordable health care services and may provide a way to detect HBV earlier on, saving many lives in the process.
