5 citations · 10 across the 6 of their papers we have counts for
6 papers
Learning a Continuous Sepsis Severity Score Without Hour-by-Hour Supervision: A Two-Site Retrospective Study
Kevin Zhu, Ryan Zhang, Baraa Abed +18
Currently used sepsis severity indices rely on fixed variables and weights established decades ago, which are coarsely discretized and calibrated to a cohort that no longer reflect…
Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning
Mohammadamin Moradi, Runyu Jiang, Yingzi Liu +6
High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual treatment planning expertise. T…
Patient-Specific Deep Reinforcement Learning for Automatic Replanning in Head-and-Neck Cancer Proton Therapy
Malvern Madondo, Yuan Shao, Yingzi Liu +3
Anatomical changes during intensity-modulated proton therapy (IMPT) for head-and-neck cancer (HNC) can shift Bragg peaks, risking tumor underdosing and organ-at-risk overdosing. Tr…
Learning Control Policies of Hodgkin-Huxley Neuronal Dynamics
Malvern Madondo, Deepanshu Verma, Lars Ruthotto +1
We present a neural network approach for closed-loop deep brain stimulation (DBS). We cast the problem of finding an optimal neurostimulation strategy as a control problem. In this…
A SWAT-based Reinforcement Learning Framework for Crop Management
Malvern Madondo, Muneeza Azmat, Kelsey Dipietro +5
Crop management involves a series of critical, interdependent decisions or actions in a complex and highly uncertain environment, which exhibit distinct spatial and temporal variat…
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management
Muneeza Azmat, Malvern Madondo, Kelsey Dipietro +5
Climate change, population growth, and water scarcity present unprecedented challenges for agriculture. This project aims to forecast soil moisture using domain knowledge and machi…