Lymphoma

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters.

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs...

AI-assisted tracking of worldwide non-pharmaceutical interventions for COVID-19.

The Coronavirus disease 2019 (COVID-19) global pandemic has transformed almost every facet of human ...

Emerging methods for the characterization of ischemic heart disease: ultrafast Doppler angiography, micro-CT, photon-counting CT, novel MRI and PET techniques, and artificial intelligence.

After an ischemic event, disruptive changes in the healthy myocardium may gradually develop and may ...

Artificial neural networks versus LASSO regression for the prediction of long-term survival after surgery for invasive IPMN of the pancreas.

Prediction of long-term survival in patients with invasive intraductal papillary mucinous neoplasm (...

Application of Artificial Neural Network as a nonhazardous alternative on kinetic analysis and modeling for green synthesis of cobalt nanocatalyst from Ocimum tenuiflorum.

The present paper is dedicated to analyze non-hazardous kinetic behaviour and modelling of green syn...

Application of deep learning as a noninvasive tool to differentiate muscle-invasive bladder cancer and non-muscle-invasive bladder cancer with CT.

OBJECTIVE: To construct a deep-learning convolution neural network (DL-CNN) system for the different...

D-MONA: A dilated mixed-order non-local attention network for speaker and language recognition.

Attention-based convolutional neural network (CNN) models are increasingly being adopted for speaker...

Prevention of non-recurrent laryngeal nerve injury in robotic thyroidectomy: imaging and technique.

INTRODUCTION: The aim of this report was to summarize observations, evaluate the feasibility, provid...

Genetic-fuzzy logic model for a non-invasive measurement of a stroke volume.

BACKGROUND: Despite the importance of stroke volume readings in understanding the work of the cardio...

Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model.

BACKGROUND: Differential diagnosis of primary central nervous system lymphoma (PCNSL) and glioblasto...

Deep learning-based reconstruction may improve non-contrast cerebral CT imaging compared to other current reconstruction algorithms.

OBJECTIVES: To evaluate image quality and reconstruction times of a commercial deep learning reconst...

Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning.

Elucidating functionality in non-coding regions is a key challenge in human genomics. It has been sh...

The adoption of cryptocurrency as a disruptive force: Deep learning-based dual stage structural equation modelling and artificial neural network analysis.

In recent years, the growth of cryptocurrency has undergone an enormous increase in cryptocurrency m...

Sign function and ANN based pole placement for computing interval controls.

This paper deals with estimation of interval controls for interval Linear Time Invariant (LTI) plant...

A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers.

Brain signals refer to the biometric information collected from the human brain. The research on bra...

Should Peritoneal Re-Approximation Be Performed After Transperitoneal Robot-Assisted Radical Prostatectomy?

The aim of the study is to examine the effect of peritoneal re-approximation or non-approximation o...

Comparison of performance of a deep learning-based mobile application with non-dermatologist physicians in the diagnosis of common skin diseases.

Data-efficient and weakly supervised computational pathology on whole-slide images.

Deep-learning methods for computational pathology require either manual annotation of gigapixel whol...

Rapid and non-destructive spectroscopic method for classifying beef freshness using a deep spectral network fused with myoglobin information.

A simple, novel, rapid, and non-destructive spectroscopic method that employs the deep spectral netw...

Weakly supervised deep learning for determining the prognostic value of F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type.

PURPOSE: To develop a weakly supervised deep learning (WSDL) method that could utilize incomplete/mi...

Non-touch ureteral manipulation of single J ureteral catheterization for robot-assisted cystectomy with intracorporeal ileal conduit.