Machine learning algorithm identifies undiagnosed episodes of pertussis
Experts at Quinten Health have developed a supervised machine learning algorithm to identify undiagnosed episodes of pertussis in adolescents and adults reporting acute respiratory illness. As pertussis is often misidentified, misdiagnosed or misreported, it is complex to assess its incidence rate in the above-mentioned populations. The aim was therefore to better estimate the incidence in […]
Developing a machine learning algorithm to detect undiagnosed pertussis episodes
Quinten Health has developed a machine learning algorithm to identify misdiagnosed or undiagnosed episodes of whooping cough in patients diagnosed with acute respiratory illness. The team used elements from clinician notes such as observed symptoms, and demographic information from electronic care records from Optum Humedica, a US population-based database. Although tetanus-diphtheria-acellular pertussis (Tdap) vaccines for […]
