Hematology

Lymphoma

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

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Showing 1261-1281 of 8,999 articles
Mean-square stabilization of impulsive neural networks with mixed delays by non-fragile feedback involving random uncertainties.

In this paper, we consider a class of neural networks with mixed delays and impulsive interferences....

Comparison of Two-Port and Three-Port Approaches in Robotic Lobectomy for Non-Small Cell Lung Cancer.

BACKGROUND: Robot-assisted lobectomy has been used to treat non-small cell lung cancer and usually u...

Detecting the sources of chemicals in the Black Sea using non-target screening and deep learning convolutional neural networks.

The Black Sea is an important ecosystem, which is affected by various anthropogenic pressures, such ...

Identification of early invisible acute ischemic stroke in non-contrast computed tomography using two-stage deep-learning model.

Although non-contrast computed tomography (NCCT) is the recommended examination for the suspected a...

Deep learning with multiresolution handcrafted features for brain MRI segmentation.

The segmentation of magnetic resonance (MR) images is a crucial task for creating pseudo computed to...

Deep Learning-Based Non-Intrusive Commercial Load Monitoring.

Commercial load is an essential demand-side resource. Monitoring commercial loads helps not only com...

Non-Deep Active Learning for Deep Neural Networks.

One way to improve annotation efficiency is active learning. The goal of active learning is to selec...

Non-iterative learning machine for identifying CoViD19 using chest X-ray images.

CoViD19 is a novel disease which has created panic worldwide by infecting millions of people around ...

Application of image processing and soft computing strategies for non-destructive estimation of plum leaf area.

Plant leaf area (LA) is a key metric in plant monitoring programs. Machine learning methods were use...

Non-Intrusive Fish Weight Estimation in Turbid Water Using Deep Learning and Regression Models.

Underwater fish monitoring is the one of the most challenging problems for efficiently feeding and h...

Predicting poor glycemic control during Ramadan among non-fasting patients with diabetes using artificial intelligence based machine learning models.

AIMS: This study aims to predict poor glycemic control during Ramadan among non-fasting patients wit...

Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is characterized by reduced cardiac output, as well as thinning and enl...

Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders.

Causal discovery from observational data is a fundamental problem in science. Though the linear non-...

Deep learning-based microarray cancer classification and ensemble gene selection approach.

Malignancies and diseases of various genetic origins can be diagnosed and classified with microarray...

Two stream Non-Local CNN-LSTM network for the auxiliary assessment of mental retardation.

At present, the assessment of mental retardation is mainly based on clinical interview, which requir...

A Machine Learning Approach for Predicting Non-Suicidal Self-Injury in Young Adults.

Artificial intelligence techniques were explored to assess the ability to anticipate self-harming be...

Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI.

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is a...

Oblique and rotation double random forest.

Random Forest is an ensemble of decision trees based on the bagging and random subspace concepts. As...

Systems Drug Discovery for Diffuse Large B Cell Lymphoma Based on Pathogenic Molecular Mechanism via Big Data Mining and Deep Learning Method.

Diffuse large B cell lymphoma (DLBCL) is an aggressive heterogeneous disease. The most common subtyp...

Disturbance Observer-Based Minimum Entropy Control for a Class of Disturbed Non-Gaussian Stochastic Systems.

In this article, a novel control algorithm is developed for a class of nonlinear stochastic systems ...

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