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The ability to detect adverse drug events (ADEs) in electronic health records (EHRs) is useful in many medical applications, such as alerting systems that indicate when an ADE-specific diagnosis code should be assigned. Automating the detection of ADEs can be attempted by applying machine learning to existing, labeled EHR data. How to do this in an effective manner is, however, an open question. The...
The enormous amounts of data that are continuously recorded in electronic health record systems offer ample opportunities for data science applications to improve healthcare. There are, however, challenges involved in using such data for machine learning, such as high dimensionality and sparsity, as well as an inherent heterogeneity that does not allow the distinct types of clinical data to be treated...
Adverse drug events (ADEs) are grossly under-reported in electronic health records (EHRs). This could be mitigated by methods that are able to detect ADEs in EHRs, thereby allowing for missing ADE-specific diagnosis codes to be identified and added. A crucial aspect of constructing such systems is to find proper representations of the data in order to allow the predictive modeling to be as accurate...
Electronic health records (EHRs) provide a potentially valuable source of information for pharmacovigilance. However, adverse drug events (ADEs), which can be encoded in EHRs with specific diagnosis codes, are heavily under-reported. To provide more accurate estimates for drug safety surveillance, machine learning systems that are able to detect ADEs could be used to identify and suggest missing ADE-specific...
Although electronic health records (EHRs) have recently become an important data source for drug safety signals detection, which is usually evaluated in clinical trials, the use of such data is often prohibited by dimensionality and available computer resources. Currently, several methods for reducing dimensionality are developed, used and evaluated within the medical domain. While these methods perform...
Rheumatoid arthritis (RA) is a chronic disease that affects the joints, often those in a person's wrists, fingers, and feet. In contrast to FDA-approved anti-RA drugs, Tripterygium wilfordii Hook F (TwHF), a traditional Chinese medicine (TCM), featured as multi-targeting, have been acknowledged with notable anti-RA effects although the pharmacology is unclear. In this work, we investigated the therapeutic...
Traditional virtual screening in the grid needs chemists to upload small molecule files and collect the results manually, which cannot implement docking and collection of results automatically. This caused heavy workload to chemists. In this paper, we took advantage of Hadoop platform in the massive data storage. We stored and managed small molecule files and docking results files using HDFS. In addition,...
In this study, the gene encoding purine nucleoside phosphorylase (PNPase) from Bacillus subtilis W168 was identified, cloned and expressed in Bacillus subtilis AG208. The gene encodes a polypeptide of 233 amino acids with a calculated molecular weight of 25,018 Da. The enzyme activity of the recombinant protein (AGPNP) was analyzed by temperature and pH perturbation difference spectra. Results showed...
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