首页|Jiangxi University of Finance and Economics Reports Findings in HIV/AIDS (Development of a predictive machine learning model for pathogen profiles in patients with secondary immunodeficiency)
Jiangxi University of Finance and Economics Reports Findings in HIV/AIDS (Development of a predictive machine learning model for pathogen profiles in patients with secondary immunodeficiency)
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New research on Immune System Diseases and Conditions - HIV/AIDS is the subject of a report. According to news reporting out of Jiangxi, People’s Republic of China, by NewsRx editors, research stated, “Secondary immunodeficiency can arise from various clinical conditions that include HIV infection, chronic diseases, malignancy and long-term use of immunosuppressives, which makes the suffering patients susceptible to all types of pathogenic infections. Other than HIV infection, the possible pathogen profiles in other aetiology-induced secondary immunodeficiency are largely unknown.” Our news journalists obtained a quote from the research from the Jiangxi University of Finance and Economics, “Medical records of the patients with secondary immunodeficiency caused by various aetiologies were collected from the First Affiliated Hospital of Nanchang University, China. Based on these records, models were developed with the machine learning method to predict the potential infectious pathogens that may inflict the patients with secondary immunodeficiency caused by various disease conditions other than HIV infection. Several metrics were used to evaluate the models’ performance. A consistent conclusion can be drawn from all the metrics that Gradient Boosting Machine had the best performance with the highest accuracy at 91.01%, exceeding other models by 13.48, 7.14, and 4.49% respectively.”
JiangxiPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesHIV/AIDSHealth and MedicineImmune System Diseases and ConditionsMachine LearningPrimate LentivirusesRNA VirusesRetroviridaeVertebrate VirusesViral Sexually Transmitted Diseases and Conditions
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