BMC medical informatics and decision making
Feb 18, 2019
BACKGROUND: Increasing life expectancy results in more elderly people struggling with age related diseases and functional conditions. This poses huge challenges towards establishing new approaches for maintaining health at a higher age. An important ...
Laboratory investigation; a journal of technical methods and pathology
Feb 15, 2019
Accumulation of abnormal tau in neurofibrillary tangles (NFT) occurs in Alzheimer disease (AD) and a spectrum of tauopathies. These tauopathies have diverse and overlapping morphological phenotypes that obscure classification and quantitative assessm...
Time-dependent data collected in studies of Alzheimer's disease usually has missing and irregularly sampled data points. For this reason time series methods which assume regular sampling cannot be applied directly to the data without a pre-processing...
IEEE journal of biomedical and health informatics
Feb 13, 2019
The diagnosis of type 2 diabetes (T2D) at an early stage has a key role for an adequate T2D integrated management system and patient's follow-up. Recent years have witnessed an increasing amount of available electronic health record (EHR) data and ma...
OBJECTIVES: Distinguishing between kidney stones and phleboliths can constitute a diagnostic challenge in patients undergoing unenhanced low-dose CT (LDCT) for acute flank pain. We sought to investigate the accuracy of radiomics and a machine-learnin...
OBJECTIVES: Stereotactic radiosurgery (SRS) is a minimally invasive modality for the treatment of trigeminal neuralgia (TN). Outcome prediction of this modality is very important for proper case selection. The aim of this study was to create artifici...
The utility of a prediction model depends on its generalizability to patients drawn from different but related populations. We explored whether a semi-supervised learning model could improve the generalizability of colorectal cancer (CRC) risk predic...
OBJECTIVE: Isocitrate dehydrogenase 1 (IDH1) mutation status is an independent favorable prognostic factor for glioblastoma (GBM) and is usually determined by sequencing or immunohistochemistry. An accurate prediction of IDH1 mutation status via noni...
Journal of cancer research and clinical oncology
Feb 4, 2019
PURPOSE: Reliable and accurate predictive models are necessary to drive the success of radiomics. Our aim was to identify the optimal radiomics-based machine learning method for isocitrate dehydrogenase (IDH) genotype prediction in diffuse gliomas.
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