The interpretation of next generation sequencing is a big challenge. In order to improve the molecular diagnosis of the patient, we developed the AI_Variant prioritizer, a machine learning based variant prioterization system that can help to prioritize candidate variants for human disease. This module highlighted the possible disease causing variants to help clinician to increase the disease diagnostic yield and decrease the load of manpower.

The is AI_Variant prioritizer was a machine learning based module that can facilitate variant prioritization. It added the value of our previous produce - MViewer, that can increase the diagnostic yield shorten time to find candidate variants. It is optimized by integrate with text mining machine learning to improve the variant interpretation efficiency.

The software can help in precision medicine, pharmacogenomics, diagnosis of genetic diseases, risk factor prediction, cancercardiovascular risk evaluation. It will facilitate the development of healthcare system.