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Data Mining

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Contextualized medication event extraction with striding NER and multi-turn QA.

Journal of biomedical informatics
This paper describes contextualized medication event extraction for automatically identifying medication change events with their contexts from clinical notes. The striding named entity recognition (NER) model extracts medication name spans from an i...

PathologyBERT - Pre-trained Vs. A New Transformer Language Model for Pathology Domain.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Pathology text mining is a challenging task given the reporting variability and constant new findings in cancer sub-type definitions. However, successful text mining of a large pathology database can play a critical role to advance 'big data' cancer ...

Implementation of hybrid wind speed prediction model based on different data mining and signal processing approaches.

Environmental science and pollution research international
Accurate estimation of wind speed (WS) data, which greatly influences meteorological parameters, plays a vital role in the safe operation and optimization of the power system and water resource management. The study's main aim is to combine artificia...

PhenoBERT: A Combined Deep Learning Method for Automated Recognition of Human Phenotype Ontology.

IEEE/ACM transactions on computational biology and bioinformatics
Automated recognition of Human Phenotype Ontology (HPO) terms from clinical texts is of significant interest to the field of clinical data mining. In this study, we develop a combined deep learning method named PhenoBERT for this purpose. PhenoBERT u...

Automated assembly of molecular mechanisms at scale from text mining and curated databases.

Molecular systems biology
The analysis of omic data depends on machine-readable information about protein interactions, modifications, and activities as found in protein interaction networks, databases of post-translational modifications, and curated models of gene and protei...

Predicting heart failure onset in the general population using a novel data-mining artificial intelligence method.

Scientific reports
We aimed to identify combinations of clinical factors that predict heart failure (HF) onset using a novel limitless-arity multiple-testing procedure (LAMP). We also determined if increases in numbers of predictive combinations of factors increases th...

B-LBConA: a medical entity disambiguation model based on Bio-LinkBERT and context-aware mechanism.

BMC bioinformatics
BACKGROUND: The main task of medical entity disambiguation is to link mentions, such as diseases, drugs, or complications, to standard entities in the target knowledge base. To our knowledge, models based on Bidirectional Encoder Representations from...

Identification of Drug Compounds for Capsular Contracture Based on Text Mining and Deep Learning.

Plastic and reconstructive surgery
BACKGROUND: Capsular contracture is a common and unpredictable complication after breast implant placement. Currently, the pathogenesis of capsular contracture is unclear, and the effectiveness of nonsurgical treatment is still doubtful. The authors'...

Efficient Selection of Gaussian Kernel SVM Parameters for Imbalanced Data.

Genes
For medical data mining, the development of a class prediction model has been widely used to deal with various kinds of data classification problems. Classification models especially for high-dimensional gene expression datasets have attracted many r...