Technology in cancer research & treatment
Jan 1, 2021
This study aimed to explore the ability of texture parameters combining with machine learning methods in distinguishing intrahepatic cholangiocarcinoma (ICCA) and hepatic lymphoma (HL). A total of 28 patients with HL and 101 patients with ICCA were...
Cervical cancer radiotherapy is often complicated by significant variability in the quality and consistency of treatment plans. Knowledge-based planning (KBP), which utilizes prior patient data to correlated achievable optimal dosimetry with patient-...
PURPOSE: This study aimed to evaluate the diagnostic value of a support vector machine (SVM) model built with texture features based on standard 2-[F]fluoro-2-deoxy-D-glucose (F-FDG) PET in patients with solitary pulmonary nodules (SPNs) at a volume ...
BACKGROUND: Prognostic modeling in health care has been predominantly statistical, despite a rapid growth of literature on machine-learning approaches in biological data analysis. We aim to assess the relative importance of variables in predicting ov...
Clinical and translational gastroenterology
Mar 1, 2020
OBJECTIVES: A superficial nonampullary duodenal epithelial tumor (SNADET) is defined as a mucosal or submucosal sporadic tumor of the duodenum that does not arise from the papilla of Vater. SNADETs rarely metastasize to the lymph nodes, and most can ...
PURPOSE: For patients with early-stage breast cancer, predicting the risk of metastatic relapse is of crucial importance. Existing predictive models rely on agnostic survival analysis statistical tools (eg, Cox regression). Here we define and evaluat...
BACKGROUND: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hype...
PURPOSE: The prediction of clinical outcomes for patients with cancer is central to precision medicine and the design of clinical trials. We developed and validated machine-learning models for three important clinical end points in patients with adva...
IMPORTANCE: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncologist work force does not meet growing global demand. One key physician task in RT planning involves tumor segmentation for targeting, which requires s...
OBJECTIVE: Prophylactic central lymph node dissection(CLND) is a controversial issue in papillary thyroid microcarcinoma( PTMC) patients without lymphatic metastasis. Artificial neural network(ANN) has been proposed as an alternative statistical tech...
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