Lymphoma

Characterizing Autoimmune Disease-associated Diffuse Large B-cell Lymphoma in a SEER-Medicare Cohort.

BACKGROUND: Severe immune dysregulation such as seen in autoimmune (AI) disease is known to act as a significant risk factor for diffuse large B-cell lymphoma (DLBCL). However, little is known about the demographics or clinical outcomes of DLBCL that arises in the setting of AI disease.

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

Prostate cancer (PCa) is a major cause of death since ancient time documented in Egyptian Ptolemaic mummy imaging. PCa detection is critical to personalized medicine and varies considerably under an MRI scan. 172 patients with 2,602 morphologic images (axial 2D T2-weighted imaging) of the prostate were obtained. A deep learning with deep convolutional neural network (DCNN) and a non-deep learning ...

An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India.

Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, car...

Machine Learning Improves Risk Stratification After Acute Coronary Syndrome.

The accurate assessment of a patient's risk of adverse events remains a mainstay of clinical care. Commonly used risk metrics have been based on logis...

Protracted severe systemic cytomegalovirus disease in an immunosuppressed patient with ulcerative colitis.

A 33-year-old man with ulcerative colitis presented with 5-day history of fever, night sweats, abdominal pain and increased stool frequency. He was on...

Robust artificial neural network for reliability and sensitivity analyses of complex non-linear systems.

Artificial Neural Networks (ANNs) are commonly used in place of expensive models to reduce the computational burden required for uncertainty quantific...

Predicting hemispheric dominance for language production in healthy individuals using support vector machine.

We used a Support Vector Machine (SVM) classifier to assess hemispheric pattern of language dominance of 47 individuals categorized as non-typical for...

DRMDA: deep representations-based miRNA-disease association prediction.

Recently, microRNAs (miRNAs) are confirmed to be important molecules within many crucial biological processes and therefore related to various complex...

Non-proliferative diabetic retinopathy symptoms detection and classification using neural network.

Diabetic retinopathy (DR) causes blindness in the working age for people with diabetes in most countries. The increasing number of people with diabete...

SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound.

Identifying and interpreting fetal standard scan planes during 2-D ultrasound mid-pregnancy examinations are highly complex tasks, which require years...

A new near-lossless EEG compression method using ANN-based reconstruction technique.

Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compressio...

Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

BACKGROUND AND PURPOSE: Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid un...

Comparison of Machine Learning Approaches for Prediction of Advanced Liver Fibrosis in Chronic Hepatitis C Patients.

BACKGROUND/AIM: Using machine learning approaches as non-invasive methods have been used recently as an alternative method in staging chronic liver di...

Systematic analysis of non-structural protein features for the prediction of PTM function potential by artificial neural networks.

Post-translational modifications (PTMs) provide an extensible framework for regulation of protein behavior beyond the diversity represented within the...

Artificial neural network-based model enhances risk stratification and reduces non-invasive cardiac stress imaging compared to Diamond-Forrester and Morise risk assessment models: A prospective study.

BACKGROUND: Coronary artery disease (CAD) accounts for more than half of all cardiovascular events. Stress testing remains the cornerstone for non-inv...

Gradient Boosted Decision Tree Classification of Endophthalmitis Versus Uveitis and Lymphoma from Aqueous and Vitreous IL-6 and IL-10 Levels.

PURPOSE: To investigate the effectiveness of gradient boosting to classify endophthalmitis versus uveitis and lymphoma by intraocular cytokine levels.

Artificial neural network modelling of continuous wet granulation using a twin-screw extruder.

Computational modelling of twin-screw granulation was conducted by using an artificial neural network (ANN) approach. Various ANN configurations were ...

Prediction of skin sensitization potency using machine learning approaches.

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from su...

A Robotic Platform to Study the Foreflipper of the California Sea Lion.

The California sea lion (Zalophus californianus), is an agile and powerful swimmer. Unlike many successful swimmers (dolphins, tuna), they generate mo...

A Novel Microspheres Formulation of Puerarin: Pharmacokinetics Study and In Vivo Pharmacodynamics Evaluations.

The aim of this study was to investigate the pharmacokinetics and pharmacodynamics of puerarin loaded carboxymethyl chitosan microspheres (Pue-CCMs). ...