AIMC Topic: Deep Learning

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Deep learning-guided design of dynamic proteins.

Science (New York, N.Y.)
Deep learning has advanced the design of static protein structures, but the controlled conformational changes that are hallmarks of natural signaling proteins have remained inaccessible to de novo design. Here, we describe a general deep learning-gui...

Whole-body CT-to-PET synthesis using a customized transformer-enhanced GAN.

Physics in medicine and biology
. Positron emission tomography with 2-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed tomography (18F-FDG PET-CT) is a multi-modality medical imaging technique widely used for screening and diagnosis of lesions and tumors, in which, CT...

Recognizing artery segments on carotid ultrasonography using embedding concatenation of deep image and vision-language models.

Physics in medicine and biology
Evaluating large artery atherosclerosis is critical for predicting and preventing ischemic strokes. Ultrasonographic assessment of the carotid arteries is the preferred first-line examination due to its ease of use, noninvasive, and absence of radiat...

Evaluating machine- and deep learning approaches for artifact detection in infant EEG: classifier performance, certainty, and training size effects.

Biomedical physics & engineering express
Electroencephalography (EEG) is essential for studying infant brain activity but is highly susceptible to artifacts due to infants' movements and physiological variability. Manual artifact detection is labor-intensive and subjective, underscoring the...

On factors that influence deep learning-based dose prediction of head and neck tumors.

Physics in medicine and biology
This study investigates key factors influencing deep learning-based dose prediction models for head and neck cancer radiation therapy. The goal is to evaluate model accuracy, robustness, and computational efficiency, and to identify key components ne...

Molecular insights fast-tracked: AI in biosynthetic pathway research.

Natural product reports
Covering: 2000 to 2025This review explores the potential of artificial intelligence (AI) in addressing challenges and accelerating molecular insights in biosynthetic pathway research, which is crucial for developing bioactive natural products with ap...

Deep learning-based model for difficult transfemoral access prediction compared with human assessment in stroke thrombectomy.

Journal of neurointerventional surgery
BACKGROUND: In mechanical thrombectomy (MT), extracranial vascular tortuosity is among the main determinants of procedure duration and success. Currently, no rapid and reliable method exists to identify the anatomical features precluding fast and sta...

Application of deep learning models in the pathological classification and staging of esophageal cancer: A focus on Wave-Vision Transformer.

World journal of gastroenterology
BACKGROUND: Esophageal cancer is the sixth most common cancer worldwide, with a high mortality rate. Early prognosis of esophageal abnormalities can improve patient survival rates. The progression of esophageal cancer follows a sequence from esophagi...

FasNet: a hybrid deep learning model with attention mechanisms and uncertainty estimation for liver tumor segmentation on LiTS17.

Scientific reports
Liver cancer, especially hepatocellular carcinoma (HCC), remains one of the most fatal cancers globally, emphasizing the critical need for accurate tumor segmentation to enable timely diagnosis and effective treatment planning. Traditional imaging te...

Towards precision agriculture tea leaf disease detection using CNNs and image processing.

Scientific reports
In this study, we introduce a groundbreaking deep learning (DL) model designed for the precise task of classifying common diseases in tea leaves, leveraging advanced image analysis techniques. Our model is distinguished by its complex multi-layer arc...