AIMC Topic: Smoking

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Pulmonologists-level lung cancer detection based on standard blood test results and smoking status using an explainable machine learning approach.

Scientific reports
Lung cancer (LC) remains the primary cause of cancer-related mortality, largely due to late-stage diagnoses. Effective strategies for early detection are therefore of paramount importance. In recent years, machine learning (ML) has demonstrated consi...

Identification of Biomarkers and Molecular Pathways Implicated in Smoking and COVID-19 Associated Lung Cancer Using Bioinformatics and Machine Learning Approaches.

International journal of environmental research and public health
Lung cancer (LC) is a significant global health issue, with smoking as the most common cause. Recent epidemiological studies have suggested that individuals who smoke are more susceptible to COVID-19. In this study, we aimed to investigate the influe...

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.

NPJ systems biology and applications
Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks inform...

Deep learning identifies histopathologic changes in bladder cancers associated with smoke exposure status.

PloS one
Smoke exposure is associated with bladder cancer (BC). However, little is known about whether the histologic changes of BC can predict the status of smoke exposure. Given this knowledge gap, the current study investigated the potential association be...

Machine learning computational model to predict lung cancer using electronic medical records.

Cancer epidemiology
BACKGROUND: Lung cancer (LC) screening using low-dose computed tomography (CT) is recommended according to standard risk criteria or personalized risk calculators. Machine learning (ML) models that can predict disease risk are an emerging method in m...

Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors.

BMC medical informatics and decision making
OBJECTIVE: To develop and validate machine learning models for predicting coronary artery disease (CAD) within a Taiwanese cohort, with an emphasis on identifying significant predictors and comparing the performance of various models.

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

BMC medical research methodology
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...

Machine learning based assessment of preclinical health questionnaires.

International journal of medical informatics
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...

Influence of Voice Interactive Educational Robot Combined with Artificial Intelligence for the Development of Adolescents.

Computational intelligence and neuroscience
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...

Mapping the evidence on identity processes and identity-related interventions in the smoking and physical activity domains: a scoping review protocol.

BMJ open
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...