Despite effective medications, rates of uncontrolled glucose levels in type 2 diabetes remain high. We aimed to test the utility of machine learning applied to big data in identifying the potential role of concomitant drugs not taken for diabetes whi...
Corpus selection bias in international relations research presents an epistemological problem: How do we know what we know? Most social science research in the field of text analytics relies on English language corpora, biasing our ability to underst...
With the increase in the amount of text information in different real-life applications, automatic text-summarization systems become more predominant in extracting relevant information. In the current study, we formulated the problem of extractive te...
BACKGROUND: Free text in electronic health records (EHR) may contain additional phenotypic information beyond structured (coded) information. For major health events - heart attack and death - there is a lack of studies evaluating the extent to which...
BACKGROUND: Significant amounts of health data are stored as free-text within clinical reports, letters, discharge summaries and notes. Busy clinicians have limited time to read such large amounts of free-text and are at risk of information overload ...
Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Network...
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...
Neural networks : the official journal of the International Neural Network Society
Nov 2, 2019
The learning problem from imbalanced data sets poses a major challenge in data mining community. Although conventional support vector machine can generally show relatively robust performance in dealing with the classification problems of imbalanced d...
BACKGROUND: Readmission after discharge from a hospital is disruptive and costly, regardless of the reason. However, it can be particularly problematic for psychiatric patients, so predicting which patients may be readmitted is critically important b...
We present the coronary artery disease (CAD) database, a comprehensive resource, comprising 126 papers and 68 datasets relevant to CAD diagnosis, extracted from the scientific literature from 1992 and 2018. These data were collected to help advance r...