This year the Mobilize Center supported 6 students to attend The Machine Learning for Healthcare Conference (MLHC) at Stanford University on August 17-18, 2018.
Congratulations to Jeeheh Oh, Jacob Fauber, Bryan Lim, Xinyuan Zhang, Bryce Woodworth, and Zelun Luo! We welcome you to read their papers below:
Bryan Lim, Oxford University. Disease-Atlas: Navigating Disease Trajectories using Deep Learning
Bryce Woodworth, UC San Diego. Preference Learning in Assistive Robotics: Observational Repeated Inverse Reinforcement Learning
Jacob Fauber, UC Riverside. Modeling “Presentness” of Electronic Health Record Data to Improve Patent State Estimation
Jeeheh Oh, University of Michigan. Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks
Xinyuan Zhang, Duke University. Multi-Label Learning from Medical Plain Text with Convolutional Residual Models
Zelun Luo, Stanford University (PI: Fei Fei). Computer Vision-based Descriptive Analytics of Seniors’ Daily Activities for Long-term Health Monitoring