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...
Temporal relations are crucial in constructing a timeline over the course of clinical care, which can help medical practitioners and researchers track the progression of diseases, treatments and adverse reactions over time. Due to the rapid adoption ...
Social media has been identified as a promising potential source of information for pharmacovigilance. The adoption of social media data has been hindered by the massive and noisy nature of the data. Initial attempts to use social media data have rel...
OBJECTIVE: To comparatively evaluate a range of Natural Language Processing (NLP) approaches for Information Extraction (IE) of low-prevalence concepts in clinical notes on the example of decline of insulin therapy recommendation by patients.
BACKGROUND: Rare diseases (RD) result in a wide variety of clinical presentations, and this creates a significant diagnostic challenge for health care professionals. We hypothesized that there exist a set of consistent and shared phenomena among all ...
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