Primary Care

Smoking & Tobacco

Latest AI and machine learning research in smoking & tobacco for healthcare professionals.

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Showing 106-126 of 3,112 articles
The application of artificial intelligence in health communication development: A scoping review.

This scoping review explores the integration of Artificial Intelligence (AI) with communication, beh...

Identifying Topics Around Nicotine Gum: A Machine Learning Approach with Twitter Data.

BACKGROUND: Nicotine gum products from brands like Lucy and Rogue are relatively new arrivals to the...

Regression prediction of tobacco chemical components during curing based on color quantification and machine learning.

Color is one of the most important indicators to characteristic the quality of tobacco, which is str...

Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Bag-Level Classifier is a Good Instance-Level Teacher.

Multiple Instance Learning (MIL) has demonstrated promise in Whole Slide Image (WSI) classification....

A first step towards a machine learning-based framework for bloodstain classification in forensic science.

Bloodstains found at a crime scene can help estimate the events that occurred during the crime. Reco...

WISE: Efficient WSI selection for active learning in histopathology.

Deep neural network (DNN) models have been applied to a wide variety of medical image analysis tasks...

Identifying predictors of multi-year cannabis vaping in U.S. Young adults using machine learning.

INTRODUCTION: Increasing number of current cannabis users report using a vaporized form of cannabis ...

Using deep learning and pretreatment EEG to predict response to sertraline, bupropion, and placebo.

OBJECTIVE: Predicting an individual's response to antidepressant medication remains one of the most ...

The Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Study.

BACKGROUND: Social media posts that portray vaping in positive social contexts shape people's percep...

A Comparison of Three Automated Root-Knot Nematode Egg Counting Approaches Using Machine Learning, Image Analysis, and a Hybrid Model.

spp. (root-knot nematodes [RKNs]) are a major threat to a wide range of agricultural crops worldwid...

SeqAFNet: A Beat-Wise Sequential Neural Network for Atrial Fibrillation Classification in Adhesive Patch-Type Electrocardiographs.

Due to their convenience, adhesive patch-type electrocardiographs are commonly used for arrhythmia s...

Twistable and Stretchable Nasal Patch for Monitoring Sleep-Related Breathing Disorders Based on a Stacking Ensemble Learning Model.

Obstructive sleep apnea syndrome disrupts sleep, destroys the homeostasis of biological systems such...

Prediction of non-muscle invasive bladder cancer recurrence using deep learning of pathology image.

We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscl...

Epidemiological breast cancer prediction by country: A novel machine learning approach.

Breast cancer remains a significant contributor to cancer-related deaths among women globally. We se...

A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images.

Eyelid malignant melanoma (MM) is a rare disease with high mortality. Accurate diagnosis of such dis...

Predicting the Hallucinogenic Potential of Molecules Using Artificial Intelligence.

The development of new drugs addressing serious mental health and other disorders should avoid the p...

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

Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is ...

Automatic Detection and Assessment of Freezing of Gait Manifestations.

Freezing of gait (FOG) is an episodic and highly disabling symptom of Parkinson's disease (PD). Alth...

STC-UNet: renal tumor segmentation based on enhanced feature extraction at different network levels.

Renal tumors are one of the common diseases of urology, and precise segmentation of these tumors pla...

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