Primary Care

Smoking & Tobacco

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

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AI-Driven Feature Selection Using Only Survey Variable Descriptions: Large Language Models Identify Adolescent Vaping Predictors

Objective: To evaluate the effectiveness of various Large Language Models (LLMs) in identifying reli...

VisualAD: Language-Free Zero-Shot Anomaly Detection via Vision Transformer

Zero-shot anomaly detection (ZSAD) requires detecting and localizing anomalies without access to tar...

Local-Global Prompt Learning via Sparse Optimal Transport

Few-shot adaptation of vision-language models (VLMs) like CLIP typically relies on learning textual ...

CONSTANT: Towards High-Quality One-Shot Handwriting Generation with Patch Contrastive Enhancement and Style-Aware Quantization

One-shot styled handwriting image generation, despite achieving impressive results in recent years, ...

PatchCue: Enhancing Vision-Language Model Reasoning with Patch-Based Visual Cues

Vision-Language Models (VLMs) have achieved remarkable progress on a wide range of challenging multi...

Sex-stratified Integrated Analysis of US lung Cancer Mortality, 1994-2020

Importance: Lung cancer mortality in the United States has fallen substantially in recent decades, y...

The Inductive Bias of Convolutional Neural Networks: Locality and Weight Sharing Reshape Implicit Regularization

We study how architectural inductive bias reshapes the implicit regularization induced by the edge-o...

Locality-Attending Vision Transformer

Vision transformers have demonstrated remarkable success in classification by leveraging global self...

Adaptive Prototype-based Interpretable Grading of Prostate Cancer

Prostate cancer being one of the frequently diagnosed malignancy in men, the rising demand for biops...

Weakly Supervised Patch Annotation for Improved Screening of Diabetic Retinopathy

Diabetic Retinopathy (DR) requires timely screening to prevent irreversible vision loss. However, it...

MoECLIP: Patch-Specialized Experts for Zero-shot Anomaly Detection

The CLIP model's outstanding generalization has driven recent success in Zero-Shot Anomaly Detection...

Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection

DINO models provide rich patch-level representations that have recently enabled strong performance i...

Any Resolution Any Geometry: From Multi-View To Multi-Patch

Joint estimation of surface normals and depth is essential for holistic 3D scene understanding, yet ...

MoECLIP: Patch-Specialized Experts for Zero-shot Anomaly Detection

The CLIP model's outstanding generalization has driven recent success in Zero-Shot Anomaly Detection...

Cannabis Use Documentation within the Electronic Health Record: A Use Case for Natural Language Processing Methods

Introduction: Recreational and medical cannabis use (CU) information is often available within the e...

Latent attention on masked patches for flow reconstruction

Vision transformers have demonstrated outstanding performance on image generation applications, but ...

NICO-RAG: Multimodal Hypergraph Retrieval-Augmented Generation for Understanding the Nicotine Public Health Crisis

The nicotine addiction public health crisis continues to be pervasive. In this century alone, the to...

Learning Accurate Segmentation Purely from Self-Supervision

Accurately segmenting objects without any manual annotations remains one of the core challenges in c...

Footprint-Guided Exemplar-Free Continual Histopathology Report Generation

Rapid progress in vision-language modeling has enabled pathology report generation from gigapixel wh...

Fixed Anchors Are Not Enough: Dynamic Retrieval and Persistent Homology for Dataset Distillation

Decoupled dataset distillation (DD) compresses large corpora into a few synthetic images by matching...

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