Knowledge graphs and disease tropism prediction using Graph convolution neural network

Date: May 22, 2020

Speaker: Alok Jha, PhD. Instructor at Stanford Cardiovascular Institute

Bio

Alokkumar Jha, Ph.D., is a translational researcher working into healthcare data science and disease modeling using multi-dimensional omics and diagnostic imaging data. He holds background with tumorigenesis, metastasis, tumor evolution and cell-cell communication. His earlier research yielded clinically actionable biomarkers for gynecologic cancers, breast cancer, pancreatic cancer, multiple myeloma, and prostate cancer. He primarily focused on building the prediction model using artificial intelligence and deep learning for clinical patient stratification and drug dosage balancing. He also developed several novel methods for biomarker discovery such as graph motif mining, Kirchoff's law traversal, deep convolution neural network, and the semantic web. His recent research is focused on explaining mosaicism genetics for cardiac amyloidosis and multiple myeloma. [https://med.stanford.edu/profiles/alokkumar-jha]