Hematology

Lymphoma

Latest AI and machine learning research in lymphoma for healthcare professionals.

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Showing 1072-1092 of 8,999 articles
Non-endoscopic Applications of Machine Learning in Gastric Cancer: A Systematic Review.

PURPOSE: Gastric cancer is an important health burden characterized by high prevalence and mortality...

Non-invasive arterial blood pressure measurement and SpO estimation using PPG signal: a deep learning framework.

BACKGROUND: Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial rol...

Fovea-UNet: detection and segmentation of lymph node metastases in colorectal cancer with deep learning.

BACKGROUND: Colorectal cancer is one of the most serious malignant tumors, and lymph node metastasis...

Prediction of lymphoma response to CAR T cells by deep learning-based image analysis.

Clinical prognostic scoring systems have limited utility for predicting treatment outcomes in lympho...

Deep learning for artery-vein classification in optical coherence tomography angiography.

Major retinopathies can differentially impact the arteries and veins. Traditional fundus photography...

Avenues for non-conventional robotics technology applications in the food industry.

Robots in manufacturing alleviate hazardous environmental conditions, reduce the physical/mental str...

The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.

Artificial Intelligence and Machine learning have been widely used in various fields of mathematical...

Deep learning-assisted LI-RADS grading and distinguishing hepatocellular carcinoma (HCC) from non-HCC based on multiphase CT: a two-center study.

OBJECTIVES: To develop a deep learning (DL) method that can determine the Liver Imaging Reporting an...

Non-traditional data sources in obesity research: a systematic review of their use in the study of obesogenic environments.

BACKGROUND: The complex nature of obesity increasingly requires a comprehensive approach that includ...

Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-Local Spatial-Temporal Similarity.

We present compact and effective deep convolutional neural networks (CNNs) by exploring properties o...

Non-invasive localization of the ventricular excitation origin without patient-specific geometries using deep learning.

Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categori...

Gigapixel end-to-end training using streaming and attention.

Current hardware limitations make it impossible to train convolutional neural networks on gigapixel ...

Intelligent solution predictive networks for non-linear tumor-immune delayed model.

In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustra...

Stochastic momentum methods for non-convex learning without bounded assumptions.

Stochastic momentum methods are widely used to solve stochastic optimization problems in machine lea...

Deep learning-assisted model-based off-resonance correction for non-Cartesian SWI.

PURPOSE: Patient-induced inhomogeneities in the static magnetic field cause distortions and blurring...

Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives.

The measurement of physiologic pressure helps diagnose and prevent associated health complications. ...

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