AIMC Topic: Smoking

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Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier.

Journal of medical systems
Cervical cancer is the fourth most communal malignant disease amongst women worldwide. In maximum circumstances, cervical cancer indications are not perceptible at its initial stages. There are a proportion of features that intensify the threat of em...

Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.

World neurosurgery
BACKGROUND: Machine learning (ML) has been increasingly used in medicine and neurosurgery. We sought to determine whether ML models can distinguish ruptured from unruptured aneurysms and identify features associated with rupture.

An adaptive Kalman filtering algorithm based on back-propagation (BP) neural network applied for simultaneously detection of exhaled CO and NO.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
A compact high-resolution spectroscopic sensor using a thermoelectrically (TE) cooled continuous-wave (CW) room temperature (RT) quantum cascade laser (QCL) was demonstrated for simultaneous measurements of exhaled carbon monoxide (CO) and nitrous ox...

Detection of smoking status from retinal images; a Convolutional Neural Network study.

Scientific reports
Cardiovascular diseases are directly linked to smoking habits, which has both physiological and anatomical effects on the systemic and retinal circulations, and these changes can be detected with fundus photographs. Here, we aimed to 1- design a Conv...

Application of Machine Learning to Identify Clustering of Cardiometabolic Risk Factors in U.S. Adults.

Diabetes technology & therapeutics
The aim of this study is to compare some machine learning methods with traditional statistical parametric analyses using logistic regression to investigate the relationship of risk factors for diabetes and cardiovascular (cardiometabolic risk) for U...

Leveraging Electronic Dental Record Data to Classify Patients Based on Their Smoking Intensity.

Methods of information in medicine
BACKGROUND: Smoking is an established risk factor for oral diseases and, therefore, dental clinicians routinely assess and record their patients' detailed smoking status. Researchers have successfully extracted smoking history from electronic health ...

Applications of machine learning in addiction studies: A systematic review.

Psychiatry research
This study aims to provide a systematic review of the applications of machine learning methods in addiction research. In this study, multiple searches on MEDLINE, Embase and the Cochrane Database of Systematic Reviews were performed. 23 full-text art...

Blood Biochemistry Analysis to Detect Smoking Status and Quantify Accelerated Aging in Smokers.

Scientific reports
There is an association between smoking and cancer, cardiovascular disease and all-cause mortality. However, currently, there are no affordable and informative tests for assessing the effects of smoking on the rate of biological aging. In this study ...

Performance of machine-learning algorithms to pattern recognition and classification of hearing impairment in Brazilian farmers exposed to pesticide and/or cigarette smoke.

Environmental science and pollution research international
The use of pesticides has been increasing in agriculture, leading to a public health problem. The aim of this study was to evaluate ototoxic effects in farmers who were exposed to cigarette smoke and/or pesticides and to identify possible classificat...