AIMC Topic: Smoking

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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...
Humans Female Aged RNA-Seq Computational Biology Models, Statistical Smoking Protein Isoforms Exons Male Middle Aged Gene Expression Profiling Deep Learning ROC Curve
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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 ...
Alcohol Drinking Healthy Lifestyle China Cohort Studies Follow-Up Studies Principal Component Analysis Smoking Forecasting Prospective Studies Female Aged Aged, 80 and over Adult Male Aging Middle Aged Exercise Humans Machine Learning
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Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Scientific reports Aug 16, 2021
Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and treatment decisions. Typically, TMB is evaluated by comprehensive genomic profiling but this requires ...
Humans Female Aged ROC Curve Lung Neoplasms Staining and Labeling Carcinoma, Non-Small-Cell Lung Age Factors Area Under Curve Aged, 80 and over Adult Male Middle Aged Deep Learning Adenocarcinoma of Lung Eosine Yellowish-(YS) Hematoxylin Mutation Coloring Agents Sex Factors Datasets as Topic Smoking
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Impact of deep learning-determined smoking status on mortality of cancer patients: never too late to quit.

ESMO open Jun 3, 2021
BACKGROUND: Persistent smoking after cancer diagnosis is associated with increased overall mortality (OM) and cancer mortality (CM). According to the 2020 Surgeon General's report, smoking cessation may reduce CM but supporting evidence is not wide. ...
Smoking Smoking Cessation Prospective Studies Cross-Sectional Studies Male Neoplasms Deep Learning Humans
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Evaluation of incomplete maternal smoking data using machine learning algorithms: a study from the Medical Birth Registry of Norway.

BMC pregnancy and childbirth Nov 23, 2020
BACKGROUND: The Medical Birth Registry of Norway (MBRN) provides national coverage of all births. While retrieval of most of the information in the birth records is mandatory, mothers may refrain to provide information on her smoking status. The prop...
Humans Machine Learning Marital Status Smoking Culture Norway Adult Prevalence Registries Mothers Algorithms Pregnancy Female Educational Status Young Adult Linear Models
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Predicting Postoperative Mortality After Metastatic Intraspinal Neoplasm Excision: Development of a Machine-Learning Approach.

World neurosurgery Nov 16, 2020
OBJECTIVE: Mortality following surgical resection of spinal tumors is a devastating outcome. Naïve Bayes machine learning algorithms may be leveraged in surgical planning to predict mortality. In this investigation, we use a Naïve Bayes classificatio...
Smoking Metastasectomy Spinal Neoplasms Multivariate Analysis Odds Ratio Humans Serum Albumin Bayes Theorem Pulmonary Disease, Chronic Obstructive Mortality Ascites Male Preoperative Care Hypoalbuminemia Middle Aged Laminectomy Risk Assessment Dyspnea Machine Learning Blood Coagulation Disorders Respiration, Artificial Female Weight Loss Aged Hypertension Body Mass Index
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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 Recurrence Smoking Cessation Ecological Momentary Assessment Tobacco Smoking Female Adult Male Middle Aged Smartphone Humans Machine Learning
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Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research Sep 24, 2020
BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas...
Surveys and Questionnaires Odds Ratio Aged Diabetes Mellitus, Type 2 Humans Logistic Models Adult Alcohol Drinking Machine Learning Decision Making Medically Underserved Area Male Algorithms Regression Analysis Middle Aged Female Decision Trees China Risk Factors Area Under Curve Asian People Waist Circumference Smoking
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Machine Learning-Based DNA Methylation Score for Fetal Exposure to Maternal Smoking: Development and Validation in Samples Collected from Adolescents and Adults.

Environmental health perspectives Sep 15, 2020
BACKGROUND: Fetal exposure to maternal smoking during pregnancy is associated with the development of noncommunicable diseases in the offspring. Maternal smoking may induce such long-term effects through persistent changes in the DNA methylome, which...
Biomarkers Pregnancy Female Adult Male Humans Machine Learning Finland Adolescent DNA Methylation Smoking Prenatal Exposure Delayed Effects Maternal Exposure
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XGBoost-Based Framework for Smoking-Induced Noncommunicable Disease Prediction.

International journal of environmental research and public health Sep 7, 2020
Smoking-induced noncommunicable diseases (SiNCDs) have become a significant threat to public health and cause of death globally. In the last decade, numerous studies have been proposed using artificial intelligence techniques to predict the risk of d...
Humans Noncommunicable Diseases Artificial Intelligence Smoking Forecasting Risk Republic of Korea
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