AIMC Topic: Data Mining

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An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition.

Bioinformatics (Oxford, England)
MOTIVATION: In biomedical research, chemical is an important class of entities, and chemical named entity recognition (NER) is an important task in the field of biomedical information extraction. However, most popular chemical NER methods are based o...

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Machine learning and data mining advance predictive big data analysis in precision animal agriculture.

Journal of animal science
Precision animal agriculture is poised to rise to prominence in the livestock enterprise in the domains of management, production, welfare, sustainability, health surveillance, and environmental footprint. Considerable progress has been made in the u...

Detecting Chemotherapeutic Skin Adverse Reactions in Social Health Networks Using Deep Learning.

JAMA oncology
This study reports proof-of-principle early detection of chemotherapeutic-associated skin adverse drug reactions from social health networks using a deep learning–based signal generation pipeline to capture how patients describe cutaneous eruptions.

Use of text-mining methods to improve efficiency in the calculation of drug exposure to support pharmacoepidemiology studies.

International journal of epidemiology
BACKGROUND: Efficient generation of structured dose instructions that enable researchers to calculate drug exposure is central to pharmacoepidemiology studies. Our aim was to design and test an algorithm to codify dose instructions, applied to the NH...

Drug-drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths.

Bioinformatics (Oxford, England)
MOTIVATION: Adverse events resulting from drug-drug interactions (DDI) pose a serious health issue. The ability to automatically extract DDIs described in the biomedical literature could further efforts for ongoing pharmacovigilance. Most of neural n...

Complex Network Study of the Immune Epitope Database for Parasitic Organisms.

Current topics in medicinal chemistry
BACKGROUND: Complex network approach allows the representation and analysis of complex systems of interacting agents in an ordered and effective manner, thus increasing the probability of discovering significant properties of them. In the present stu...

iPTMnet: an integrated resource for protein post-translational modification network discovery.

Nucleic acids research
Protein post-translational modifications (PTMs) play a pivotal role in numerous biological processes by modulating regulation of protein function. We have developed iPTMnet (http://proteininformationresource.org/iPTMnet) for PTM knowledge discovery, ...

A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction.

Indian journal of pharmacology
CONTEXT: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details c...

Intelligently Applying Artificial Intelligence in Chemoinformatics.

Current topics in medicinal chemistry
The intertwining of chemoinformatics with artificial intelligence (AI) has given a tremendous fillip to the field of drug discovery. With the rapid growth of chemical data from high throughput screening and combinatorial synthesis, AI has become an i...