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Improving fold resistance prediction of HIV1 against protease and reverse transcriptase inhibitors using artificial neural networks
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Drug resistance in HIV treatment is still a worldwide problem. Predicting resistance to antiretrovirals (ARVs) before starting any treatment is important. Prediction accuracy is essential, as low-accuracy predictions increase the risk of prescribing sub-optimal drug regimens leading to patients developing resistance sooner.
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