The Human Disease Ontology (DO) (http://www.disease-ontology.org), database has undergone significant expansion in the past three years. The DO disease classification includes specific formal semantic rules to express meaningful disease models and ha...
One important aspect of precision medicine aims to deliver the right medicine to the right patient at the right dose at the right time based on the unique 'omics' features of each individual patient, thus maximizing drug efficacy and minimizing adver...
Database : the journal of biological databases and curation
Jan 1, 2019
To generate a parsimonious gene set for understanding the mechanisms underlying complex diseases, we reasoned it was necessary to combine the curation of public literature, review of experimental databases and interpolation of pathway-associated gene...
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2018
OBJECTIVE: To conduct a systematic review of deep learning models for electronic health record (EHR) data, and illustrate various deep learning architectures for analyzing different data sources and their target applications. We also highlight ongoin...
MOTIVATION: Learning probabilistic graphs over mixed data is an important way to combine gene expression and clinical disease data. Leveraging the existing, yet imperfect, information in pathway databases for mixed graphical model (MGM) learning is a...
Journal of the Royal Society, Interface
Apr 1, 2018
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine ar...
BACKGROUND: On a tide of big data, machine learning is coming to its day. Referring to huge amounts of epigenetic data coming from biological experiments and clinic, machine learning can help in detecting epigenetic features in genome, finding correl...
Studies in health technology and informatics
Jan 1, 2017
Chemical-induced disease relations (CID) are crucial in various biomedical tasks. In the CID task of Biocreative V, no classifiers with multiple kernels have been developed. In this study, a multiple kernel learning-boosting (MKLB) method is proposed...
Database : the journal of biological databases and curation
Jan 1, 2017
UNLABELLED: This article describes our work on the BioCreative-V chemical-disease relation (CDR) extraction task, which employed a maximum entropy (ME) model and a convolutional neural network model for relation extraction at inter- and intra-sentenc...