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- W4320803887 abstract "Human immunodeficiency virus infection and acquired immune deficiency syndrome (HIV/AIDS) is one of the major burdens of disease in developing countries, and the standard-of-care treatment includes prescribing antiretroviral drugs. Although 23 different drugs have been available, the treatment of AIDS remains challenging because the virus mutates very quickly which can lead to drug resistance. Predicting drug resistance before treatment is crucial for individual treatments. Taking that into account, different investigations undertaken with machine learning will be discussed." @default.
- W4320803887 created "2023-02-15" @default.
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- W4320803887 date "2022-04-12" @default.
- W4320803887 modified "2023-10-18" @default.
- W4320803887 title "Predicting HIV drug resistance using machine learning" @default.
- W4320803887 doi "https://doi.org/10.3390/mol2net-08-12473" @default.
- W4320803887 hasPublicationYear "2022" @default.
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