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Chemoradiotherapy

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Predicting Emergency Visits and Hospital Admissions During Radiation and Chemoradiation: An Internally Validated Pretreatment Machine Learning Algorithm.

JCO clinical cancer informatics
PURPOSE: Patients undergoing radiotherapy (RT) or chemoradiotherapy (CRT) may require emergency department evaluation or hospitalization. Early identification may direct preventative supportive care, improving outcomes and reducing health care costs....

A Randomized Phase 2 Trial of Prophylactic Manuka Honey for the Reduction of Chemoradiation Therapy-Induced Esophagitis During the Treatment of Lung Cancer: Results of NRG Oncology RTOG 1012.

International journal of radiation oncology, biology, physics
PURPOSE: Randomized trials have shown that honey is effective for the prevention of radiation-induced mucositis in head and neck cancer patients. Because there is no efficacious preventative for radiation esophagitis in lung cancer patients, this tri...

[A Case of Curative Resection for Advanced Pancreatic Acinar Cell Carcinoma with Liver Metastasis and Involvement of the Superior Mesenteric Artery after Chemoradiotherapy Following Systemic Chemotherapy].

Gan to kagaku ryoho. Cancer & chemotherapy
A 52-year-old man was initially diagnosed with an unresectable acinar cell carcinoma of the pancreas with liver metastasis and involvement of the superior mesenteric artery. After 5 courses of systemic chemotherapy(gemcitabine and S-1), the size of t...

A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate ...

Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.

Medical physics
PURPOSE: Machine learning classification algorithms (classifiers) for prediction of treatment response are becoming more popular in radiotherapy literature. General Machine learning literature provides evidence in favor of some classifier families (r...

Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a radiotherapy dose-limiting toxicity for locally advanced non-small cell lung cancer (LA-NSCLC). Prior studies have proposed relevant dosimetric constraints to limit this toxicity. Using machine ...

Nasopharyngeal carcinoma segmentation based on enhanced convolutional neural networks using multi-modal metric learning.

Physics in medicine and biology
Multi-modality examinations have been extensively applied in current clinical cancer management. Leveraging multi-modality medical images can be highly beneficial for automated tumor segmentation as they provide complementary information that could m...

Prediction of response after chemoradiation for esophageal cancer using a combination of dosimetry and CT radiomics.

European radiology
PURPOSE: To investigate the treatment response prediction feasibility and accuracy of an integrated model combining computed tomography (CT) radiomic features and dosimetric parameters for patients with esophageal cancer (EC) who underwent concurrent...

Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.

Magnetic resonance imaging
PURPOSE: To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with locally advanced rectal cancer (LARC) using radiomics and deep learning based on pre-treatment MRI and a mid-radiation follow-up MRI taken 3-4 weeks after the ...