AIMC Topic: Smokers

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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...
Humans Machine Learning Female Adult Poverty Motivation Smokers Smoking Cessation Text Messaging Male Middle Aged Vulnerable Populations Randomized Controlled Trials as Topic
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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...
Tomography, Emission-Computed Regression Analysis Smokers Bronchiectasis Bronchi Humans Artificial Intelligence Female Aged Middle Aged Pulmonary Disease, Chronic Obstructive Cohort Studies Male 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...
Humans Artificial Intelligence Young Adult Adult Aging Middle Aged Deep Learning Data Analysis Phenotype Female Aged Metagenomics Smokers Menopause Metagenome Computational Biology Skin Microbiota Biodiversity
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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
Early Detection of Cancer Smokers Tomography, X-Ray Computed Deep Learning Lung Neoplasms Mass Screening Humans
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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 Products Motivation Smoking Smokers Ecological Momentary Assessment Tobacco Smoking Recurrence Smoking Cessation Adult Male Middle Aged Smartphone Humans Machine Learning Female
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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...
Emotions Self Report Smokers Humans Machine Learning Smartphone
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Artificial Intelligence and Data Mining to Assess Lung Cancer Risk: Challenges and Opportunities.

Annals of internal medicine Sep 1, 2020
Humans Lung Neoplasms Smokers Early Detection of Cancer Data Mining Artificial Intelligence Deep Learning
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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).
B7-H1 Antigen Antigens, Neoplasm Adenocarcinoma Carcinoma, Non-Small-Cell Lung Mutation Forkhead Transcription Factors Carcinoembryonic Antigen Humans Lymphocytes, Tumor-Infiltrating Machine Learning Regression Analysis Female Tumor Microenvironment Male Non-Smokers Middle Aged Lung Neoplasms Smokers Carcinoma, Squamous Cell Exome Sequencing Aged Keratin-19 Aged, 80 and over Ex-Smokers Adult
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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...
ROC Curve Image Processing, Computer-Assisted Lung Neoplasms Canada Smokers Neural Networks, Computer Mass Screening Ex-Smokers Risk Assessment Artificial Intelligence Area Under Curve Disease Progression Data Analysis Models, Biological Lung Tomography, X-Ray Computed Humans Smoking Pulmonary Disease, Chronic Obstructive Cohort Studies Female Male Aged Middle Aged
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Towards a Smart Smoking Cessation App: A 1D-CNN Model Predicting Smoking Events.

Sensors (Basel, Switzerland) Feb 17, 2020
Nicotine consumption is considered a major health problem, where many of those who wish to quit smoking relapse. The problem is that overtime smoking as behaviour is changing into a habit, in which it is connected to internal (e.g., nicotine level, c...
Smoking Humans Smokers Machine Learning Smoking Cessation Male Mobile Applications
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