Machine learning techniques have recently received considerable attention, especially when used for the construction of prediction models from data. Despite their potential advantages over standard statistical methods, like their ability to model non-linear relationships and construct symbolic and interpretable models, their applications to survival analysis are at best rare, primarily because ...

OBJECTIVES The aim of this study was to investigate the prognostic value and preoperative predictors of microvascular invasion (MVI) in solitary hepatocellular carcinoma (HCC) ≤ 5 cm without macrovascular invasion. METHODS A total of 233 consecutive HCC patients underwent curative hepatectomy were included in our study. Independent risk factors influencing the prognosis were identified, and p...

The application of optical absorption spectra in prognostic prediction has hardly been investigated. We developed and evaluated a novel two dimensional absorption spectrum measurement system (TDAS) for use in early diagnosis, evaluating response to chemoradiation, and making prognostic prediction. The absorption spectra of 120 sets of normal and tumor tissues from esophageal cancer patients wer...

The updated Vienna Prediction Model for estimating recurrence risk after an unprovoked venous thromboembolism (VTE) has been developed to identify individuals at low risk for VTE recurrence in whom anticoagulation (AC) therapy may be stopped after 3 months. We externally validated the accuracy of the model to predict recurrent VTE in a prospective multicenter cohort of 156 patients aged ≥65 yea...

BackgroundPulmonary vein isolation is a widely used method to treat Atrial fibrillation (AF). However, many patients experience AF recurrence, leading repeated ablation requirements. In this study, we sought identify whether left atrial (LA) geometry can at risk of recurrence after second ablation.ObjectiveTo predict repeat using machine learning on clinical covariates and LA geometric features...

The risk of biochemical recurrence of prostate cancer among individuals who undergo radical prostatectomy for treatment is around 25%. Current clinical methods often fail at successfully predicting recurrence among patients at intermediate risk for recurrence. We used a label-free method, spatial light interference microscopy, to perform localized measurements of light scattering in prostatecto...