Mass spectrometry (MS) provides a wealth of chemical information. We combine MS with machine learning to multiple applications: breast cancer diagnosis, finding potential biomarkers in house dust, imaging fusion for high resolution MS image,tumor margin determination by lipid isomers. In summary, our techniques provide an insight into the next-generation clinical panels.

We developed an innovative technique coupling mass spectrometry data with machine learning to have breakthroughs in fields including 1) breast cancer prediction, giving an accuracy up to 80, 2) linking health status with environmental chemicals of dust, 3) Imaging fusion, giving 70 increment of biomarker discovery,4) cancer margin determination by lipid isomer.

We decided to promote commercial productswell-developed platform to the hospitals for the next generation medical treatment
(1) Convenient examination protocols for the hospital: high efficiencyaccuracy assisted by artificial intelligence.
(2) Innovative therapiesnew kits: newly discovered biomarkers.
(3) Commercial machine for disease early detection: increment survival rate.