Hematology

Lymphoma

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

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Joint correction of attenuation and scatter in image space using deep convolutional neural networks for dedicated brain F-FDG PET.

Dedicated brain positron emission tomography (PET) devices can provide higher-resolution images with...

Prediction of Long Non-Coding RNAs Based on Deep Learning.

With the rapid development of high-throughput sequencing technology, a large number of transcript se...

Machine Learning Approach to find the relation between Endometriosis, benign breast disease, cystitis and non-toxic goiter.

The exact mechanism of endometriosis is unknown. The recommendation system (RS) based on item simila...

Asynchronous event-based sampling data for impulsive protocol on consensus of non-linear multi-agent systems.

In this paper, we discuss the consensus problem of non-linear multi-agent systems where an impulsive...

Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis.

Tumour budding has been described as an independent prognostic feature in several tumour types. We r...

Non-invasive assessment of NAFLD as systemic disease-A machine learning perspective.

BACKGROUND & AIMS: Current non-invasive scores for the assessment of severity of non-alcoholic fatty...

Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations.

Several neuron types have been shown to exhibit (subthreshold) membrane potential resonance (MPR), d...

Analysis and evaluation of handwriting in patients with Parkinson's disease using kinematic, geometrical, and non-linear features.

BACKGROUND AND OBJECTIVES: Parkinson's disease is a neurological disorder that affects the motor sys...

Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics.

OBJECTIVES: To assess the performance of feed-forward back-propagation artificial neural networks (A...

Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology.

OBJECTIVE: Obstructive sleep-disordered breathing (SDB) events, unlike central events, are associate...

Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography.

Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to ...

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group...

Simulation-based deep artifact correction with Convolutional Neural Networks for limited angle artifacts.

Non-conventional scan trajectories for interventional three-dimensional imaging promise low-dose int...

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans.

State-of-the-art methods assessing pathogenic non-coding variants have mostly been characterized on ...

Finite-time cluster synchronization for a class of fuzzy cellular neural networks via non-chattering quantized controllers.

This paper considers the finite-time cluster synchronization (FTCS) of coupled fuzzy cellular neural...

Proximal detection of guide wire perforation using feature extraction from bispectral audio signal analysis combined with machine learning.

Artery perforation during a vascular catheterization procedure is a potentially life threatening eve...

Predicting centre of mass horizontal speed in low to severe swimming intensities with linear and non-linear models.

We aimed to compare multilayer perceptron (MLP) neural networks, radial basis function neural networ...

Microbiological validation of a robot for the sterile compounding of injectable non-hazardous medications in a hospital environment.

OBJECTIVES: To design and execute a comprehensive microbiological validation protocol to assess a br...

Defining and discriminating responders from non-responders following transurethral resection of the prostate.

BACKGROUND: Transurethral resection of the prostate (TURP) is the reference standard surgical treatm...

Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches.

Risk stratification (characterization) of tumors from radiology images can be more accurate and fast...

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