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Smoking & Tobacco

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

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Adversarial Patch Attacks on Deep-Learning-Based Face Recognition Systems Using Generative Adversarial Networks.

Deep learning technology has developed rapidly in recent years and has been successfully applied in ...

Tubule-U-Net: a novel dataset and deep learning-based tubule segmentation framework in whole slide images of breast cancer.

The tubule index is a vital prognostic measure in breast cancer tumor grading and is visually evalua...

Self-supervised learning-based Multi-Scale feature Fusion Network for survival analysis from whole slide images.

Understanding prognosis and mortality is critical for evaluating the treatment plan of patients. Adv...

Unusual Driver Behavior Detection in Videos Using Deep Learning Models.

Anomalous driving behavior detection is becoming more popular since it is vital in ensuring the safe...

Prediction Models for Identifying Ion Channel-Modulating Peptides via Knowledge Transfer Approaches.

Ion channels, which can be modulated by peptides, are promising drug targets for neurological, metab...

Further predictive value of lymphovascular invasion explored via supervised deep learning for lymph node metastases in breast cancer.

Lymphovascular invasion, specifically lymph-blood vessel invasion (LBVI), is a risk factor for metas...

Identify Representative Samples by Conditional Random Field of Cancer Histology Images.

Pathology analysis is crucial to precise cancer diagnoses and the succeeding treatment plan as well....

Patch-based CNN for corneal segmentation of AS-OCT images: Effect of the number of classes and image quality upon performance.

Anterior segment optical coherence tomography (AS-OCT) is a fundamental ophthalmic imaging technique...

Protocol for the operation of a breathing and vaping biomimetic robot to delineate real-time inhaled particle profile of electronic cigarettes.

We recently developed a robotic human vaping mimetic real-time particle analyzer (HUMITIPAA) to eval...

Defending Person Detection Against Adversarial Patch Attack by Using Universal Defensive Frame.

Person detection has attracted great attention in the computer vision area and is an imperative elem...

Shuffle-ResNet: Deep learning for predicting LGG IDH1 mutation from multicenter anatomical MRI sequences.

The world health organization recommended to incorporate gene information such as isocitrate dehydro...

Contrastive and Selective Hidden Embeddings for Medical Image Segmentation.

Medical image segmentation is fundamental and essential for the analysis of medical images. Although...

FAPNET: Feature Fusion with Adaptive Patch for Flood-Water Detection and Monitoring.

In satellite remote sensing applications, waterbody segmentation plays an essential role in mapping ...

Fast and scalable search of whole-slide images via self-supervised deep learning.

The adoption of digital pathology has enabled the curation of large repositories of gigapixel whole-...

Gait-ViT: Gait Recognition with Vision Transformer.

Identifying an individual based on their physical/behavioral characteristics is known as biometric r...

Blind Quality Prediction for View Synthesis Based on Heterogeneous Distortion Perception.

The quality of synthesized images directly affects the practical application of virtual view synthes...

A Robust Visual Tracking Method Based on Reconstruction Patch Transformer Tracking.

Recently, the transformer model has progressed from the field of visual classification to target tra...

Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis.

Inflammatory bowel disease (IBD) is a chronic immune-mediated disease of the gastrointestinal tract....

Clinical and Biological Significances of a Ferroptosis-Related Gene Signature in Lung Cancer Based on Deep Learning.

Acyl-CoA synthetase long-chain family member 4 (ACSL4) has been linked to the occurrence of tumors a...

High-Resolution Histopathological Image Classification Model Based on Fused Heterogeneous Networks with Self-Supervised Feature Representation.

Applying machine learning technology to automatic image analysis and auxiliary diagnosis of whole sl...

Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images.

Tumor segmentation is a fundamental task in histopathological image analysis. Creating accurate pixe...

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