Abstract: Systems and methods for deterring transmission of viruses using neural networks are disclosed. An example method includes detecting in a bodily fluid sample from a subject a set of anti-virus antibody features and generating an input vector that includes data indicative of the anti-virus antibody features of the subject. The method also includes applying the input vector to a trained neural network algorithm that is configured to generate an assigned classification to the subject. The assigned classification is one of a plurality of potential classifications of the neural network algorithm. The method also includes determining whether the pregnant subject is a suitable candidate for therapeutic intervention based on the assigned classification and, responsive to determining that the human subject is suitable, providing the therapeutic intervention to the subject to reduce risk of vertical transmission.

Abstract: Systems and methods for identifying subjects as having latent or primary herpesvirus infections and/or determining the time since the subject was exposed to or infected with a herpesvirus using machine learning algorithms are disclosed. An example method includes detecting in a bodily fluid sample from a subject a set of anti-virus antibody features and generating an input vector that includes data indicative of the anti-virus antibody features of the subject. The method also includes applying the input vector to a trained machine learning algorithm that is configured to generate an assigned classification to the subject. The assigned classification is one of a plurality of potential classifications of the machine learning algorithm.