Machine learning reveals unique COVID vaccine immune signatures in people living with HIV, with differences in antibodies, cytokines, and T cell responses.

Machine-learning models accurately pinpointed differences in immune responses in healthy controls and those living with HIV.

For doctors who dream of confronting the AIDS epidemic, past ambitions always boiled down to two main goals: prevention, or finding ways to protect people not yet exposed to HIV, through vaccines, ...

A study on almost four thousand people of African descent has identified a gene that acts as natural defense against HIV by limiting its replication in certain white blood cells. This research paves ...

How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by York University has found that not only could machine-learning models ...

The enormous genetic diversity between individual HIV-1 viruses presents a difficult hurdle for vaccine design, as the vaccine-elicited antibodies must neutralize a large range of HIV envelope (Env) ...

Machine learning models, particularly LightGBM, effectively predict hyperlipidemia in PLWH on HAART for six months, with high accuracy and area under curve values. The study's limitations include ...

Pioneering technology developed by UCL (University College London) and Africa Health Research Institute (AHRI) researchers could transform the ability to accurately interpret HIV test results, ...

“We searched for human genetic variation that associates with spontaneous control of HIV and identified a novel region in the genome that is only variable in populations of African ancestries,” says ...