AIMC Topic: Smokers

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Lysophospholipid metabolism, clinical characteristics, and artificial intelligence-based quantitative assessments of chest CT in patients with stable COPD and healthy smokers.

Scientific reports Jul 21, 2025
The specific role of lysophospholipids (LysoPLs) in the pathogenesis of chronic obstructive pulmonary disease (COPD) is not yet fully understood. We determined serum LysoPLs in 20 patients with stable COPD and 20 healthy smokers using liquid chromato...
Humans Artificial Intelligence Biomarkers Tomography, X-Ray Computed Female Case-Control Studies Lysophospholipids Smoking Smokers Lysophosphatidylcholines Aged Pulmonary Disease, Chronic Obstructive Male Middle Aged
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Testing a Machine Learning-Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial.

JMIR research protocols Apr 16, 2025
BACKGROUND: Individuals who are socioeconomically disadvantaged have high smoking rates and face barriers to participating in smoking cessation interventions. Computer-tailored health communication, which is focused on finding the most relevant messa...
Motivation Smokers Smoking Cessation Humans Text Messaging Machine Learning Female Adult Male Middle Aged Vulnerable Populations Randomized Controlled Trials as Topic Poverty
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Artificial Intelligence-based CT Assessment of Bronchiectasis: The COPDGene Study.

Radiology Dec 13, 2022
Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent...
Humans Artificial Intelligence Female Aged Pulmonary Disease, Chronic Obstructive Regression Analysis Smokers Bronchiectasis Bronchi Tomography, Emission-Computed Male Middle Aged Cohort Studies Follow-Up Studies
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Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences.

Scientific reports Feb 25, 2021
Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains to be learned about the links between the microbiome and human health. The fusion of artificial inte...
Deep Learning Computational Biology Skin Microbiota Biodiversity Young Adult Adult Aging Middle Aged Metagenomics Smokers Menopause Metagenome Humans Artificial Intelligence Data Analysis Phenotype Female Aged
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Beyond the : "Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model".

AJR. American journal of roentgenology Dec 23, 2020
Mass Screening Early Detection of Cancer Smokers Humans Tomography, X-Ray Computed Deep Learning Lung Neoplasms
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Predicting the first smoking lapse during a quit attempt: A machine learning approach.

Drug and alcohol dependence Oct 11, 2020
BACKGROUND: Just-in-time adaptive interventions (JITAI) aim to prevent smoking lapse using tailored support delivered via mobile technology in the moments when it is most needed. Effective smoking cessation JITAI rely on the development of accurate d...
Tobacco Smoking Smokers Recurrence Smoking Cessation Ecological Momentary Assessment Machine Learning Female Humans Adult Male Middle Aged Smartphone Tobacco Products Motivation Smoking
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Using Machine Learning and Smartphone and Smartwatch Data to Detect Emotional States and Transitions: Exploratory Study.

JMIR mHealth and uHealth Sep 29, 2020
BACKGROUND: Emotional state in everyday life is an essential indicator of health and well-being. However, daily assessment of emotional states largely depends on active self-reports, which are often inconvenient and prone to incomplete information. A...
Humans Machine Learning Smartphone Emotions Smokers Self Report
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Artificial Intelligence and Data Mining to Assess Lung Cancer Risk: Challenges and Opportunities.

Annals of internal medicine Sep 1, 2020
Lung Neoplasms Humans Early Detection of Cancer Artificial Intelligence Data Mining Deep Learning Smokers
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Assessment of associations between clinical and immune microenvironmental factors and tumor mutation burden in resected nonsmall cell lung cancer by applying machine learning to whole-slide images.

Cancer medicine May 12, 2020
BACKGROUND: It is unclear whether clinical factors and immune microenvironment (IME) factors are associated with tumor mutation burden (TMB) in patients with nonsmall cell lung cancer (NSCLC).
Exome Sequencing Keratin-19 Ex-Smokers Non-Smokers Regression Analysis Mutation Forkhead Transcription Factors Carcinoembryonic Antigen Smokers Antigens, Neoplasm Adenocarcinoma Carcinoma, Non-Small-Cell Lung Humans Lymphocytes, Tumor-Infiltrating Machine Learning Female Tumor Microenvironment Carcinoma, Squamous Cell Male Aged Middle Aged Aged, 80 and over Lung Neoplasms Adult B7-H1 Antigen
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Towards large-scale case-finding: training and validation of residual networks for detection of chronic obstructive pulmonary disease using low-dose CT.

The Lancet. Digital health Apr 21, 2020
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is underdiagnosed in the community. Thoracic CT scans are widely used for diagnostic and screening purposes for lung cancer. In this proof-of-concept study, we aimed to evaluate a software pipe...
Smokers Middle Aged Ex-Smokers Risk Assessment Mass Screening Humans Cohort Studies Tomography, X-Ray Computed Area Under Curve Neural Networks, Computer Disease Progression Female ROC Curve Models, Biological Artificial Intelligence Lung Aged Image Processing, Computer-Assisted Smoking Data Analysis Pulmonary Disease, Chronic Obstructive Lung Neoplasms Male Canada
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