Optimal policy determination in sequential systemic and locoregional therapy of oropharyngeal squamous carcinomas: A patient-physician digital twin dyad with deep Q-learning for treatment selection is a research paper published in medRxiv (2021). On theSindex it has a DataRank of 0. It has been cited 7 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
National Institutes of Health
Grant: 1R25EB025787-01
Fellow and Resident Radiation Oncology iNtensive Training in Imaging and Informatics to Empower Research Careers (FRONTI2ER)
National Science Foundation
Grant: 1933369
Collaborative Research: Stochastic and Dynamic Chemotherapy Planning and Dosing
National Institutes of Health
Grant: 5R01CA214825-03
SMART-ACT: Spatial Methodologic Approaches for Risk Assessment and Therapeutic Adaptation in Cancer Treatment
National Science Foundation
Grant: 1828265
MRI: Acquisition of a Composable Platform as a Service Instrument for Deep Learning & Visualization (COMPaaS DLV)
National Institutes of Health
Grant: 5P50CA097007-07
CA: Administrative Core
National Institutes of Health
Grant: 5R01DE025248-04
Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to Establish Objective Clinical Outcome Measures for Mandibular Osteoradionecrosis
National Institutes of Health
Grant: 3P30CA016672-41S4
Cancer Center Support (CORE) Grant
Fields of Study
Sustainable Development Goals