AIMC Topic: Smoking

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Application of an artificial neural network model for selection of potential lung cancer biomarkers.

Journal of breath research May 6, 2015
Determination of volatile organic compounds (VOCs) in the exhaled breath samples of lung cancer patients and healthy controls was carried out by SPME-GC/MS (solid phase microextraction- gas chromatography combined with mass spectrometry) analyses. In...
Mass Spectrometry Gas Chromatography-Mass Spectrometry Aged, 80 and over Volatile Organic Compounds Smoking Young Adult Case-Control Studies Solid Phase Microextraction Adult Biomarkers, Tumor Lung Neoplasms Breath Tests Sensitivity and Specificity Male Exhalation Adenocarcinoma Humans Middle Aged Small Cell Lung Carcinoma Carcinoma, Non-Small-Cell Lung Neural Networks, Computer Female Aged
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The application of data mining techniques to oral cancer prognosis.

Journal of medical systems Mar 22, 2015
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 ...
Sex Factors Survival Analysis Smoking Alcohol Drinking Age Factors Decision Trees Mouth Neoplasms Data Mining Humans Neural Networks, Computer Logistic Models
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Smoking Status Normalization with Cross-Encoders and SNOMED CT.

Studies in health technology and informatics May 15, 2025
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 ...
Natural Language Processing Systematized Nomenclature of Medicine Germany Smoking Humans Electronic Health Records
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Investigating the correlation between smoking and blood pressure via photoplethysmography.

Biomedical engineering online May 12, 2025
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...
Electrocardiography Blood Pressure Signal Processing, Computer-Assisted Heart Rate Smoking Humans Machine Learning Female Young Adult Adult Male Photoplethysmography
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Driver identification and fatigue detection algorithm based on deep learning.

Mathematical biosciences and engineering : MBE Feb 27, 2023
In order to avoid traffic accidents caused by driver fatigue, smoking and talking on the phone, it is necessary to design an effective fatigue detection algorithm. Firstly, this paper studies the detection algorithms of driver fatigue at home and abr...
Algorithms Deep Learning Smoking
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A Generic Semi-Supervised and Active Learning Framework for Biomedical Text Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Biomedical text classification requires having training examples labeled by clinical specialists, a process that can be costly. To address this problem, active learning incrementally selects a subset of the most informative unlabeled examples, sample...
Supervised Machine Learning Smoking Problem-Based Learning Humans Algorithms Obesity
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Verification and comparison of three prediction models of ischemic stroke in young adults based on the back propagation neural networks.

Medicine Mar 19, 2021
This work aims to explore risk factors for ischemic stroke in young adults and analyze the Traditional Vascular Risk Factors Model based on age, hypertension, diabetes, smoking history, and drinking history. Further, the Lipid Metabolism Model was an...
Risk Factors Young Adult Adult Male Humans Neural Networks, Computer Acute Kidney Injury Female Clinical Decision Rules Age Factors ROC Curve Lipoproteins Diabetes Mellitus, Type 2 Factor Analysis, Statistical Predictive Value of Tests Hypertension Ischemic Stroke Kidney Function Tests Area Under Curve Middle Aged Smoking Risk Assessment Alcohol Drinking Adolescent
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A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco Mar 16, 2020
AIMS: Most cigarette smokers want to quit smoking and more than half make an attempt every year, but less than 10% remain abstinent for at least 6 months. Evidence-based tobacco use treatment improves the likelihood of quitting, but more than two-thi...
Smoking Carbon Monoxide Smoking Cessation Cognitive Behavioral Therapy Middle Aged Treatment Outcome Cotinine Health Behavior Humans Machine Learning Female Male
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Machine Learning Approach for Predicting Past Environmental Exposures From Molecular Profiling of Post-Exposure Human Serum Samples.

Journal of occupational and environmental medicine Dec 1, 2019
OBJECTIVE: To develop an approach for a retrospective analysis of post-exposure serum samples using diverse molecular profiles.
Environmental Exposure Sex Factors Smoking Tobacco Smoke Pollution Age Factors Disease Models, Animal Mice, Inbred C57BL Cotinine Male Adolescent Support Vector Machine Humans Machine Learning Biomarkers Female Young Adult Adult Animals
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A Comparison of SVM and CNN-LSTM Based Approach for Detecting Smoke Inhalations from Respiratory signal.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Wearable sensors have successfully been used in recent studies to monitor cigarette smoking events and analyze people's smoking behavior. Respiratory inductive plethysmography (RIP) has been employed to track breathing and to identify characteristic ...
Smoke Wearable Electronic Devices Humans Support Vector Machine Neural Networks, Computer Smoking Machine Learning Plethysmography Algorithms
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