Lymphoma

Neural networks may outperform classical regressions, but only when non-linear relationships are considered.

Deep forest ensemble learning for classification of alignments of non-coding RNA sequences based on multi-view structure representations.

Non-coding RNAs (ncRNAs) play crucial roles in multiple biological processes. However, only a few nc...

A comprehensive survey on computational methods of non-coding RNA and disease association prediction.

The studies on relationships between non-coding RNAs and diseases are widely carried out in recent y...

Non-destructive acoustic screening of pineapple ripeness by unsupervised machine learning and Wavelet Kernel methods.

In a pineapple exporting factory, manual lines are usually built to screen fruits of non-ripen hitti...

Combining artificial intelligence: deep learning with Hi-C data to predict the functional effects of non-coding variants.

MOTIVATION: Although genome-wide association studies (GWASs) have identified thousands of variants f...

[Application of deep learning neural network in pathological image classification of non-inflammatory aortic membrane degeneration].

To investigate the value of deep learning in classifying non-inflammatory aortic membrane degenerat...

Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images.

BACKGROUND: Currently, only a fraction of patients with non-small cell lung cancer (NSCLC) treated w...

scCancer: a package for automated processing of single-cell RNA-seq data in cancer.

Molecular heterogeneities and complex microenvironments bring great challenges for cancer diagnosis ...

MLCDForest: multi-label classification with deep forest in disease prediction for long non-coding RNAs.

The long non-coding RNAs (lncRNAs) are subject of intensive recent studies due to its association wi...

Comparisons between Locomat and Walkbot robotic gait training regarding balance and lower extremity function among non-ambulatory chronic acquired brain injury survivors.

Lower limb rehabilitation exoskeleton robots connect with the human body in a wearable way and contr...

Deep Learning-based Propensity Scores for Confounding Control in Comparative Effectiveness Research: A Large-scale, Real-world Data Study.

BACKGROUND: Due to the non-randomized nature of real-world data, prognostic factors need to be balan...

High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status.

Clinical definitions of asthma fail to capture the heterogeneity of immune dysfunction in severe, tr...

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation.

Kinases play important roles in diverse cellular processes, including signaling, differentiation, pr...

Developing a Neural Network Model for a Non-invasive Prediction of Histologic Activity in Inflammatory Bowel Diseases.

BACKGROUND: Colonoscopy with biopsy is the "gold" standard for evaluating disease activity in inflam...

Artificial intelligence in prediction of non-alcoholic fatty liver disease and fibrosis.

Artificial intelligence (AI) has become increasingly widespread in our daily lives, including health...

Unenhanced CT texture analysis with machine learning for differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma.

Differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma (ML) remains cha...

Technology-Enabled and Artificial Intelligence Support for Pre-Visit Planning in Ambulatory Care: Findings From an Environmental Scan.

PURPOSE: Pre-visit planning (PVP) is believed to improve effectiveness, efficiency, and experience o...

Differentiation of Intrahepatic Cholangiocarcinoma and Hepatic Lymphoma Based on Radiomics and Machine Learning in Contrast-Enhanced Computer Tomography.

This study aimed to explore the ability of texture parameters combining with machine learning metho...

Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.

Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important too...

Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain ...

Security robot for the prevention of workplace violence using the Non-linear Adaptive Heuristic Mathematical Model.

BACKGROUND: Nowadays, workplace violence is found to be a mental health hazard and considered a cruc...