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Smoking & Tobacco

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

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Showing 526-546 of 2,720 articles
Bayesian network modeling: A case study of an epidemiologic system analysis of cardiovascular risk.

An extensive, in-depth study of cardiovascular risk factors (CVRF) seems to be of crucial importance...

Dec 2015 26777431
Imatinib Increases Serum Creatinine by Inhibiting Its Tubular Secretion in a Reversible Fashion in Chronic Myeloid Leukemia.

BACKGROUND: Monitoring renal function is important in imatinib-treated patients with chronic myeloid...

Dec 2015 26795084
Evaluation of the impact of Flos Daturae on rat hepatic cytochrome P450 enzymes by cocktail probe drugs.

Flos Daturae, known as "baimantuoluo" or "yangjinhua" in China, has been used for centuries in Tradi...

Dec 2015 26885208
Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching.

Automatic and reliable segmentation of the prostate is an important but difficult task for various c...

Dec 2015 26685226
Close Human Interaction Recognition Using Patch-Aware Models.

This paper addresses the problem of recognizing human interactions with close physical contact from ...

Nov 2015 26561435
Automated Extraction of Substance Use Information from Clinical Texts.

Within clinical discourse, social history (SH) includes important information about substance use (a...

Nov 2015 26958312
Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes.

The 2014 i2b2 natural language processing shared task focused on identifying cardiovascular risk fac...

Aug 2015 26318122
Multiple Sparse Representations Classification.

Sparse representations classification (SRC) is a powerful technique for pixelwise classification of ...

Jul 2015 26177106
On-water remote monitoring robotic system for estimating the patch coverage of Anabaena sp. filaments in shallow water.

An on-water remote monitoring robotic system was developed for indirectly estimating the relative de...

May 2015 25965101
Log-Spiral Keypoint: A Robust Approach toward Image Patch Matching.

Matching of keypoints across image patches forms the basis of computer vision applications, such as ...

May 2015 26074952
Structured patch model for a unified automatic and interactive segmentation framework.

We present a novel interactive segmentation framework incorporating a priori knowledge learned from ...

Jan 2015 25682219
CSV-ViT: A Vision Transformer with the Variable-sized Cortical Supervertices for Detection of Alzheimer's Disease Pathologies

Confirming Alzheimer's disease (AD) typically relies on positron emission tomography (PET), which re...

[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation

Vision-Language Models such as CLIP exhibit strong zero-shot recognition capability by aligning imag...

Channel-wise Vector Quantization

We present Channel-wise Vector Quantization (CVQ), a novel image tokenization paradigm that replaces...

Exposing Vulnerabilities in Visible-Infrared VLMs: A Unified Geometric Adversarial Framework with Cross-Task Transferability

Vision-language models (VLMs) have achieved strong performance across diverse multimodal tasks, but ...

Detection of Virus and Small Cell Patches in Foci Images Using Switchable Convolution and Feature Pyramid Networks

Accurate detection and counting of virus patches in focus-forming unit (FFU) images, also known as f...

Patch-MoE Mamba: A Patch-Ordered Mixture-of-Experts State Space Architecture for Medical Image Segmentation

CNN- and Transformer-based architectures have achieved strong performance in medical image segmentat...

SkyNative: A Native Multimodal Framework for Remote Sensing Visual Evidence Reasoning

Remote sensing vision-language models commonly rely on pretrained visual encoders to convert images ...

Patch Ensembles for Robust Salmon Re-Identification with Weak Trajectory Labels

Salmon re-identification in commercial net-pens is challenging due to large populations, which impos...

Spatial Blindness in Whole-Slide Multiple Instance Learning

Whole-slide MIL models are often called context-aware once graphs, Transform ers, or state-space mod...

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