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https://www.selleckchem.com/products/sr-717.html Our purpose was to report outcomes of elderly patients who underwent definitive treatment involving radiation therapy for esophageal cancer at our institution. We performed a retrospective review of patients aged ≥75 years with esophageal cancer treated with definitive radiation therapy (≥45 Gy) at our institution from 1997 to 2019. Acute and late Radiation Therapy Oncology Group grade 3+ toxicities were recorded. Survival was estimated using the Kaplan-Meier method. Of the 89 patients included, median age was 80 and 78% were male. Median adjusted Charlson Comorbidity Index and Karnofsky Performance Status were 5 (3-12) and 80 (50-100), respectively. The majority of cancers were adenocarcinoma (58%), distal (67%), and stage III (62%). Fifty-eight percent underwent definitive chemoradiotherapy, and one-third underwent preoperative intent chemoradiotherapy. Median prescribed dose was 50 Gy (45-66 Gy), and intensity modulated radiation therapy was used in 76%. Eighty-five percent completed the radiation thal indications are needed to reduce toxicity. Radical surgery is the most important treatment modality in gastric cancer. Preoperative or postoperative radiation therapy (RT) and perioperative chemotherapy are the treatment options that should be added to surgery. This study aimed to evaluate the overall survival (OS) and recurrence patterns by machine learning in gastric cancer cases undergoing RT. Between 2012 and 2019, the OS and recurrence patterns of 75 gastric cancer cases receiving RT ± chemotherapy at the Department of Radiation Oncology were evaluated by machine learning. Logistic regression, multilayer perceptron, XGBoost, support vector classification, random forest, and Gaussian Naive Bayes (GNB) algorithms were used to predict OS, hematogenous distant metastases, and peritoneal metastases. After the correlation analysis, the backward feature selection was performed as the variable selection method, and the

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