نتایج جستجو برای: Recurrence Prediction
تعداد نتایج: 337559 فیلتر نتایج به سال:
background: numerous studies used microarray gene expression data to extract metastasis-driving gene signatures for the prediction of breast cancer relapse. however, the accuracy and generality of the previously introduced biomarkers are not acceptable for reliable usage in independent datasets. this inadequacy is attributed to ignoring gene interactions by simple feature selection methods, due...
this paper aims to propose an effective paroxysmal atrial fibrillation (paf) predictor which is based on the analysis of the heart rate variability (hrv) signal. predicting the onset of paf, based on non-invasive techniques, is clinically important and can be invaluable in order to avoid useless therapeutic intervention and to minimize the risks for the patients. this method consists of four st...
background: using primary tumor gene expression has been shown to have the ability of finding metastasis-driving gene markers for the prediction of breast cancer recurrence (bcr). however, there are some difficulties associated with the analysis of microarray data which led to poor predictive power and inconsistency of the previously introduced gene signatures. methods: in this study a hybrid m...
Introduction: Advanced quantitative information such as radiomics features derived from magnetic resonance (MR) image may be useful for outcome prediction, prognostic models or response biomarkers in Glioblastoma (GBM). The main aim of this study was to evaluate MRI radiomics features for recurrence prediction in glioblastoma multiform. Materials and Methods:</str...
BACKGROUND/AIMS Hepatocellular carcinoma (HCC) has a very poor prognosis, due to the high incidence of tumor recurrence. As the current morphological indicators are often insufficient for therapeutic decisions, we sought to identify additional biologic indicators for early recurrence. METHODS We analyzed gene expression using a PCR-based array of 3,072 genes in 100 HCC patients. Informative g...
We developed a series of models to predict the likelihood of recurrence and the response to chemotherapy for the personalized treatment of stage I and II colorectal cancer patients. A recurrence prediction model was developed from 235 stage I/II patients. The model successfully distinguished between high-risk and low-risk groups, with a hazard ratio of recurrence of 4.66 (p < 0.0001). More impo...
The purpose of this study was to investigate the Prostate-Health-Index (PHI) for pathological outcome prediction following radical prostatectomy and also for biochemical recurrence prediction in comparison to established parameters such as Gleason-score, pathological tumor stage, resection status (R0/1) and prostate-specific antigen (PSA). Out of a cohort of 460 cases with preoperative PHI-meas...
Objective: This study aimed to identify potential risk genes and microRNAs (miRNAs) related to the recurrence risk of osteosarcoma (OS) using support vector machine (SVM) algorithm. Methods: Based on the mRNA expression profiling dataset GSE39055 and the miRNA expression profiling dataset GSE39040, differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) indiagnosti...
PURPOSE The poor prognosis of hepatocellular carcinoma (HCC) is, in part, due to the high rate of recurrence even after "curative resection" of tumors. Therefore, it is axiomatic that the development of an effective prognostic prediction model for HCC recurrence after surgery would, at minimum, help to identify in advance those who would most benefit from the treatment, and at best, provide new...
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