Accurate Prediction of Clinical Disease Progression in Patients With Advanced Fibrosis Due to NASH using a Bayesian Machine Learning Approach

Latourelle J, Tu J, Das R, Furchtgott L, Schoeberl B, Smiechowski B, Church B, Khalil I, Hayete B, Djedjos S, Nguyen T, Xiao Y, Aguilar R, Chen G, Subramnian, Myers R, Ratziu V, Nezam A, Bosch, Goodman Z, Harrison S, Sanyal A. The International Liver Congress™. Paris,...

Machine learning approach to personalized medicine in breast cancer patients: development of data-driven, personalized, causal modeling through identification and understanding of optimal treatments for predicting better disease outcomes

Kaplan, G.H., Berry, A.B., Rinn, K.J., Ellis, E.D., Birchfield, G.R., Wahl, T.A., Liu, X., Tameishi, M., Beatty, J.D., Dawson, P.L., Mehta, V.K., Holman, A., Atwood, M.K., Alexander, S., Bonham, C., Summers, L., Khalil, I., Hayete, B., Wuest, D., Zheng, W., Liu, Y.,...