Machine learning

Machine learning for the prediction of survival post-allogeneic hematopoietic cell transplantation: A single-center experience
Introduction: Prediction of outcomes following allogeneic hematopoietic cell transplantation (HCT) remains a major challenge. Machine …
Cite DOI
Spatio-temporal clustering of multi-location time series to model seasonal influenza spread
Although seasonal influenza disease spread is a spatio-temporal phenomenon, public surveillance systems aggregate data only spatially, …
Cite DOI
SuPART: supervised projective adapted resonance theory for automatic quality assurance approval of radiotherapy treatment plans
Radiotherapy is a common treatment modality for the treatment of cancer, where treatments must be carefully designed to deliver …
PDF Cite DOI
Understanding machine learning classifier decisions in automated radiotherapy quality assurance
The complexity of generating radiotherapy treatments demands a rigorous quality assurance (QA) process to ensure patient safety and to …
Cite DOI
Prediction of COVID-19 severity
Predicting of COVID-19 hospitalization, ICU, and death at the time of RT-PCR testing, days in advance of a patient seeking medical care, allowing for improved care and resource allocation
Cancer treatment planning
Automating treatment protocol selection and the design and validation of radiation treatment plans to better treat cancer
Transplant matching and survival prediction
Matching pools of kidney patients to eligible donors and predicting survival of bone marrow and liver transplants using machine learning
Pandemic modeling and planning
Predicting pandemic disease spread through very large agent-based simulations and optimizing mitigation strategies through graph theory and machine learning
Prediction of severe COVID-19 outcomes at the time testing: An anomaly detection approach
Early and effective detection of severe infection cases during a pandemic can significantly help patient prognosis and resource …
Cite DOI
Knowledge-based isocenter selection in radiosurgery planning
Purpose: We present a new method for knowledge-based isocenter selection for treatment planning in radiosurgery. Our objective is to …
Cite DOI