Abstract: The present disclosure provides methods and systems for using diagnostic feedback loops as an integrated mechanism to generate or improve machine learning classification models by using biological sample molecular data, clinical data, controlled experimental data, real-world clinical data, or a combination thereof. The feedback loops described herein may receive a combination of biological sample molecular data, clinical data, controlled experimental data, and real-world clinical data which may be processed using the feedback loop, and a machine learning classifier may be generated or revised as an output of the feedback loop. Applications of the diagnostic feedback loops may include disease screening, diagnosis, prognosis, and treatment determination.