Computer-based systems and methods utilizing computer vision deep learning techniques for acquiring rapid diagnostic test results

A method, comprising:

• instructing, by at least one processor, a client device to guide, via a display application, a patient to perform at least one rapid diagnostic test (RDT) selected from a plurality of RDTs to measure at least one biomarker;
• receiving, by the at least one processor, from a camera module, controlling at least one camera coupled to the client device, at least one first image stream of the at least one RDT;
• wherein the at least one RDT comprises at least one test region displaying at least one visual indicator;
• applying, by the at least one processor, at least one computer vision deep learning technique of a deep learning module to identify a plurality of device features of the at least one RDT in the at least one first image stream;
• selecting, by the at least one processor, based on at least one first reference image, at least one imaging directing command for the at least one camera to capture at least one second image stream;
• wherein the at least one second image stream includes the at least one test region;
• instructing, by the at least one processor, to implement the at least one imaging directing command to automatically generate the at least one second image stream;
• receiving, by the at least one processor, the at least one second image stream from the at least one camera adjusted with the at least one imaging directing command;
• executing, by the at least one processor, the at least one computer vision deep learning technique of the deep learning module to:
• identify a plurality of device features of the at least one test region in the at least one second image stream, and
• classify, based on the plurality of device features of the at least one test region, at least one second image in the at least one second image stream to at least one second reference image in a corpus of reference images of the at least one test region;
• and
• determining, by the at least one processor, based on the at least one visual indicator of an RDT result in the at least one second reference image, a presence, a level, or both, of the at least one biomarker.