AIMC Topic: Cardiovascular Diseases

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A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases.

Journal of biomedical informatics
Automated phenotype identification plays a critical role in cohort selection and bioinformatics data mining. Natural Language Processing (NLP)-informed classification techniques can robustly identify phenotypes in unstructured medical notes. In this ...

Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge.

Journal of biomedical informatics
This paper describes the use of an agile text mining platform (Linguamatics' Interactive Information Extraction Platform, I2E) to extract document-level cardiac risk factors in patient records as defined in the i2b2/UTHealth 2014 challenge. The appro...

Using local lexicalized rules to identify heart disease risk factors in clinical notes.

Journal of biomedical informatics
Heart disease is the leading cause of death globally and a significant part of the human population lives with it. A number of risk factors have been recognized as contributing to the disease, including obesity, coronary artery disease (CAD), hyperte...

Non-redundant association rules between diseases and medications: an automated method for knowledge base construction.

BMC medical informatics and decision making
BACKGROUND: The widespread use of electronic health records (EHRs) has generated massive clinical data storage. Association rules mining is a feasible technique to convert this large amount of data into usable knowledge for clinical decision making, ...

A novel neural-inspired learning algorithm with application to clinical risk prediction.

Journal of biomedical informatics
Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for...

Heterogeneous cardiovascular effects of sodium-glucose cotransporter 2 inhibitors in type 2 diabetes: a causal forest and target trial emulation study.

European journal of preventive cardiology
AIMS: Evidence is limited as to who benefit the most from sodium-glucose cotransporter 2 inhibitors (SGLT2i), especially among people without elevated cardiovascular disease (CVD) risk. To address this knowledge gap, we investigated the heterogeneity...

Sex-specific body fat distribution predicts cardiovascular ageing.

European heart journal
BACKGROUND AND AIMS: Cardiovascular ageing is a progressive loss of physiological reserve, modified by environmental and genetic risk factors, that contributes to multi-morbidity due to accumulated damage across diverse cell types, tissues, and organ...

Innovative application of confocal Raman spectroscopy and Machine learning in cardiovascular diseases identification.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Myocardial hypertrophy and heart failure are leading causes of mortality in cardiovascular diseases, yet current diagnostic techniques lack the resolution to monitor molecular changes effectively. In this study, we employed confocal Raman spectroscop...