AIMC Topic: Hodgkin Disease

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Integrative bioinformatics and machine learning identify key crosstalk genes and immune interactions in head and neck cancer and Hodgkin lymphoma.

Scientific reports May 6, 2025
Head and neck squamous cell carcinoma (HNSCC) is a highly aggressive malignancy with complex molecular underpinnings. Hodgkin lymphoma (HL), another distinct cancer type, shares several biological characteristics with HNSCC, particularly regarding im...
Gene Expression Regulation, Neoplastic Squamous Cell Carcinoma of Head and Neck Head and Neck Neoplasms Hodgkin Disease Gene Expression Profiling Protein Interaction Maps Gene Regulatory Networks Computational Biology Humans Machine Learning Prognosis Tumor Microenvironment Biomarkers, Tumor
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Survival trend and outcome prediction for pediatric Hodgkin and non-Hodgkin lymphomas based on machine learning.

Clinical and experimental medicine Jun 18, 2024
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...
Male Infant Adolescent Child, Preschool Child Nomograms Lymphoma, Non-Hodgkin Survival Analysis Hodgkin Disease Female Risk Factors Young Adult Adult Humans Machine Learning Prognosis
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Outcome-based multiobjective optimization of lymphoma radiation therapy plans.

The British journal of radiology Sep 30, 2021
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...
Hodgkin Disease Female Humans Young Adult Lymphoma Artificial Intelligence Adult Treatment Outcome Organs at Risk Radiotherapy Planning, Computer-Assisted Image Interpretation, Computer-Assisted Radiotherapy Dosage
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Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with FDG-PET/CT.

Scientific reports May 17, 2021
To develop an artificial intelligence (AI)-based method for the detection of focal skeleton/bone marrow uptake (BMU) in patients with Hodgkin's lymphoma (HL) undergoing staging with FDG-PET/CT. The results of the AI in a separate test group were comp...
Young Adult Adult Male Middle Aged Adolescent Child Multimodal Imaging Positron Emission Tomography Computed Tomography Biopsy Artificial Intelligence Female Aged Aged, 80 and over Humans Hodgkin Disease Neural Networks, Computer Skeleton Bone Marrow Musculoskeletal System Biological Transport Radiopharmaceuticals Fluorodeoxyglucose F18
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Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG-PET/CT in Hodgkin and non-Hodgkin lymphomas.

Clinical physiology and functional imaging Oct 3, 2018
BACKGROUND: 18F-FDG-PET/CT has become a standard for assessing treatment response in patients with lymphoma. A subjective interpretation of the scan based on the Deauville 5-point scale has been widely adopted. However, inter-observer variability due...
Mediastinum Young Adult Hodgkin Disease Adult Male Middle Aged Radiopharmaceuticals Humans Treatment Outcome Adolescent Female Lymphoma, Non-Hodgkin Liver Reproducibility of Results Neural Networks, Computer Image Interpretation, Computer-Assisted Predictive Value of Tests Aged Retrospective Studies Automation Positron Emission Tomography Computed Tomography Aged, 80 and over Fluorodeoxyglucose F18
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Logic Learning Machine and standard supervised methods for Hodgkin's lymphoma prognosis using gene expression data and clinical variables.

Health informatics journal Jun 27, 2016
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...
Gene Expression Humans Hodgkin Disease Machine Learning Prognosis Cluster Analysis Decision Trees
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Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text.

Journal of the American Medical Informatics Association : JAMIA Apr 9, 2015
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...
Natural Language Processing Data Mining Hodgkin Disease Humans Electronic Health Records Narration Unsupervised Machine Learning
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Development of time to event prediction models using federated learning.

BMC medical research methodology May 26, 2025
BACKGROUND: In a wide range of diseases, it is necessary to utilize multiple data sources to obtain enough data for model training. However, performing centralized pooling of multiple data sources, while protecting each patients' sensitive data, can ...
Humans Models, Statistical Survival Analysis Machine Learning Proportional Hazards Models Algorithms Hodgkin Disease Computer Simulation Federated Learning Time Factors
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Epidemiology characteristics and clinical outcomes of composite Hodgkin lymphoma and diffuse large B-cell lymphoma using machine learning.

The oncologist Apr 4, 2025
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....
Aged Aged, 80 and over Young Adult Adult Lymphoma, Large B-Cell, Diffuse Humans Machine Learning Prognosis Female Child SEER Program Hodgkin Disease Male Middle Aged Adolescent Incidence
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Determining health care cost drivers in older Hodgkin lymphoma survivors using interpretable machine learning methods.

Journal of managed care & specialty pharmacy Apr 1, 2025
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...
Humans Machine Learning SEER Program Health Care Costs Cancer Survivors Hodgkin Disease Male Retrospective Studies United States Female Medicare Aged Health Expenditures Aged, 80 and over
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