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Hodgkin Disease

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Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxe...

Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

Health informatics journal
This study evaluates the performance of a set of machine learning techniques in predicting the prognosis of Hodgkin's lymphoma using clinical factors and gene expression data. Analysed samples from 130 Hodgkin's lymphoma patients included a small set...

Outcome-based multiobjective optimization of lymphoma radiation therapy plans.

The British journal of radiology
At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse events in cancer survivors. The radiation oncologist weighs numerous disease and patient-level factors when considering the expected risk-benefit ratio...

De Novo Identification and Visualization of Important Cell Populations for Classic Hodgkin Lymphoma Using Flow Cytometry and Machine Learning.

American journal of clinical pathology
OBJECTIVES: Automated classification of flow cytometry data has the potential to reduce errors and accelerate flow cytometry interpretation. We desired a machine learning approach that is accurate, is intuitively easy to understand, and highlights th...

Survival trend and outcome prediction for pediatric Hodgkin and non-Hodgkin lymphomas based on machine learning.

Clinical and experimental medicine
Pediatric Hodgkin and non-Hodgkin lymphomas differ from adult cases in biology and management, yet there is a lack of survival analysis tailored to pediatric lymphoma. We analyzed lymphoma data from 1975 to 2018, comparing survival trends between 7,8...

Epidemiology characteristics and clinical outcomes of composite Hodgkin lymphoma and diffuse large B-cell lymphoma using machine learning.

The oncologist
Composite lymphoma (CL) is rare. We conducted an analysis of 53 329 cases of diffuse large B-cell lymphoma (DLBCL), 17,916 cases of Hodgkin lymphoma (HL), and 869 cases of composite HL and DLBCL from the SEER database diagnosed between 2000 and 2019....

Determining health care cost drivers in older Hodgkin lymphoma survivors using interpretable machine learning methods.

Journal of managed care & specialty pharmacy
BACKGROUND: The cost of health care for patients with Hodgkin lymphoma (HL) is projected to rise, making it essential to understand expenditure drivers across different demographics, including the older adult population. Although older HL patients co...