AIMC Topic: Smoking

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Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study.

BMC medical research methodology May 17, 2024
BACKGROUND: Smoking is a critical risk factor responsible for over eight million annual deaths worldwide. It is essential to obtain information on smoking habits to advance research and implement preventive measures such as screening of high-risk ind...
Humans Neural Networks, Computer Machine Learning Middle Aged Denmark Natural Language Processing Smoking Electronic Health Records Female Male
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Machine learning based assessment of preclinical health questionnaires.

International journal of medical informatics Oct 21, 2023
BACKGROUND: Within modern health systems, the possibility of accessing a large amount and a variety of data related to patients' health has increased significantly over the years. The source of this data could be mobile and wearable electronic system...
Smoking Pregnancy Complications Humans Tobacco Smoking Machine Learning Risk Assessment Surveys and Questionnaires Pregnancy Female
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Influence of Voice Interactive Educational Robot Combined with Artificial Intelligence for the Development of Adolescents.

Computational intelligence and neuroscience Oct 6, 2022
In the context of multicultural information, to explore and analyze the use effect of voice interactive educational robot in the classroom of adolescent students, and the physical and mental impact of movie characters on adolescent students, and to l...
Adolescent Behavior Robotics Smoking Reproducibility of Results Surveys and Questionnaires Adolescent Motion Pictures Humans Artificial Intelligence
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Mapping the evidence on identity processes and identity-related interventions in the smoking and physical activity domains: a scoping review protocol.

BMJ open Jul 13, 2022
INTRODUCTION: Smoking and insufficient physical activity (PA), independently but especially in conjunction, often lead to disease and (premature) death. For this reason, there is need for effective smoking cessation and PA-increasing interventions. I...
Humans Scoping Reviews As Topic Exercise Artificial Intelligence Mass Screening Research Design Smoking Delivery of Health Care
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Covariate adjustment of spirometric and smoking phenotypes: The potential of neural network models.

PloS one May 11, 2022
To increase power and minimize bias in statistical analyses, quantitative outcomes are often adjusted for precision and confounding variables using standard regression approaches. The outcome is modeled as a linear function of the precision variables...
Forced Expiratory Volume Smoking Spirometry Neural Networks, Computer Phenotype
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Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study.

Scientific reports Nov 26, 2021
We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models ...
Cognition Disorders Smoking Life Style Mortality Middle Aged Cohort Studies United Kingdom Risk Factors Aged Male Databases, Factual Female Humans Machine Learning
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Numerical investigations of the nonlinear smoke model using the Gudermannian neural networks.

Mathematical biosciences and engineering : MBE Nov 15, 2021
These investigations are to find the numerical solutions of the nonlinear smoke model to exploit a stochastic framework called gudermannian neural works (GNNs) along with the optimization procedures of global/local search terminologies based genetic ...
Reproducibility of Results Nonlinear Dynamics Neural Networks, Computer Smoking Algorithms
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Predicting obesity and smoking using medication data: A machine-learning approach.

Pharmacoepidemiology and drug safety Oct 17, 2021
PURPOSE: Administrative health datasets are widely used in public health research but often lack information about common confounders. We aimed to develop and validate machine learning (ML)-based models using medication data from Australia's Pharmace...
Humans Male Cohort Studies Machine Learning Female Smoking Child ROC Curve Obesity
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Improved prediction of smoking status via isoform-aware RNA-seq deep learning models.

PLoS computational biology Oct 11, 2021
Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk fac...
Protein Isoforms Exons Computational Biology Models, Statistical Smoking Deep Learning ROC Curve RNA-Seq Aged Humans Male Female Middle Aged Gene Expression Profiling
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A machine learning-based biological aging prediction and its associations with healthy lifestyles: the Dongfeng-Tongji cohort.

Annals of the New York Academy of Sciences Sep 3, 2021
This study aims to establish a biological age (BA) predictor and to investigate the roles of lifestyles on biological aging. The 14,848 participants with the available information of multisystem measurements from the Dongfeng-Tongji cohort were used ...
Principal Component Analysis Smoking Alcohol Drinking China Cohort Studies Follow-Up Studies Healthy Lifestyle Aged, 80 and over Adult Male Aging Middle Aged Exercise Prospective Studies Female Aged Humans Machine Learning Forecasting
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