AIMC Topic: Smoking

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High-throughput and sensitive analysis of urinary heterocyclic aromatic amines using isotope-dilution liquid chromatography-tandem mass spectrometry and robotic sample preparation system.

Analytical and bioanalytical chemistry
Heterocyclic aromatic amines (HCAA) are listed by the US Food and Drug Administration (FDA) as harmful or potentially harmful constituents of tobacco smoke. However, quantifying HCAA exposure is challenging. In this study, we developed a sensitive, p...

Classifying smoking urges via machine learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Smoking is the largest preventable cause of death and diseases in the developed world, and advances in modern electronics and machine learning can help us deliver real-time intervention to smokers in novel ways. In this pape...

The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA.

NeuroImage
Resting state functional network connectivity (rsFNC) derived from functional magnetic resonance (fMRI) imaging is emerging as a possible biomarker to identify several brain disorders. Recently it has been pointed out that methods used to preprocess ...

Bayesian network modeling: A case study of an epidemiologic system analysis of cardiovascular risk.

Computer methods and programs in biomedicine
An extensive, in-depth study of cardiovascular risk factors (CVRF) seems to be of crucial importance in the research of cardiovascular disease (CVD) in order to prevent (or reduce) the chance of developing or dying from CVD. The main focus of data an...

Family income per capita, age, and smoking status are predictors of low fiber intake in residents of São Paulo, Brazil.

Nutrition research (New York, N.Y.)
We hypothesized that dietary total fiber intake may be less than recommendations and that the intake of total, soluble, and insoluble fiber may be associated with demographic, lifestyle, and socioeconomic factors. Data were drawn from the Health Surv...

The application of data mining techniques to oral cancer prognosis.

Journal of medical systems
This study adopted an integrated procedure that combines the clustering and classification features of data mining technology to determine the differences between the symptoms shown in past cases where patients died from or survived oral cancer. Two ...

Smoking Status Normalization with Cross-Encoders and SNOMED CT.

Studies in health technology and informatics
Accurately documenting smoking status is essential for clinical decision-making and patient care. However, smoking status information is often only available in clinical narratives. Mapping smoking-related terms to standardized terminologies such as ...

Investigating the correlation between smoking and blood pressure via photoplethysmography.

Biomedical engineering online
Smoking has been widely identified for its detrimental effects on human health, particularly on the cardiovascular health. The prediction of these effects can be anticipated by monitoring the dynamic changes in vital signs and other physiological sig...