Lymphoma

Effect of an artificial intelligence-assisted tool on non-valvular atrial fibrillation anticoagulation management in primary care: protocol for a cluster randomized controlled trial.

BACKGROUND: Atrial fibrillation (AF) is one of the most common cardiac arrhythmia diseases. Thromboe...

Click-on fluorescence detectors: using robotic surgical instruments to characterize molecular tissue aspects.

Fluorescence imaging is increasingly being implemented in surgery. One of the drawbacks of its appli...

The Usage of ANN for Regression Analysis in Visible Light Positioning Systems.

In this paper, we study the design aspects of an indoor visible light positioning (VLP) system that ...

Machine learning model for classification of predominantly allergic and non-allergic asthma among preschool children with asthma hospitalization.

OBJECTIVE: Asthma is the most frequent chronic airway illness in preschool children and is difficult...

A content-based image retrieval system for the diagnosis of lymphoma using blood micrographs: An incorporation of deep learning with a traditional learning approach.

Lymphomas, or cancers of the lymphatic system, account for around half of all blood cancers diagnose...

Non-Invasive Measurement Using Deep Learning Algorithm Based on Multi-Source Features Fusion to Predict PD-L1 Expression and Survival in NSCLC.

BACKGROUND: Programmed death-ligand 1 (PD-L1) assessment of lung cancer in immunohistochemical assay...

Optimizing Latent Distributions for Non-Adversarial Generative Networks.

The generator in generative adversarial networks (GANs) is driven by a discriminator to produce high...

Photo-induced non-volatile VO phase transition for neuromorphic ultraviolet sensors.

In the quest for emerging in-sensor computing, materials that respond to optical stimuli in conjunct...

Deep learning derived automated ASPECTS on non-contrast CT scans of acute ischemic stroke patients.

Ischemic stroke is the most common type of stroke, ranked as the second leading cause of death world...

Deep learning and non-invasive assessment of significant fibrosis: does adding more toppings improve the flavor of prediction?

Machine learning versus logistic regression for prognostic modelling in individuals with non-specific neck pain.

PURPOSE: Prognostic models play an important clinical role in the clinical management of neck pain d...

Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods.

Linear dependence of variables is a commonly used assumption in most diagnostic systems for which ma...

Pre-germinated brown rice alleviates non-alcoholic fatty liver disease induced by high fructose and high fat intake in rat.

In past researches, we had been proved the action mechanism of pre-germinated brown rice (PGBR) to t...

A Differential Privacy Strategy Based on Local Features of Non-Gaussian Noise in Federated Learning.

As an emerging artificial intelligence technology, federated learning plays a significant role in pr...

The Value of Artificial Intelligence Film Reading System Based on Deep Learning in the Diagnosis of Non-Small-Cell Lung Cancer and the Significance of Efficacy Monitoring: A Retrospective, Clinical, Nonrandomized, Controlled Study.

OBJECTIVE: To explore the value of artificial intelligence (AI) film reading system based on deep le...

Semisolid Pharmaceutical Product Characterization Using Non-invasive X-ray Microscopy and AI-Based Image Analytics.

This work reports the use of X-ray microscopy (XRM) imaging to characterize the microstructure of se...

A radiomics-boosted deep-learning model for COVID-19 and non-COVID-19 pneumonia classification using chest x-ray images.

PURPOSE: To develop a deep learning model design that integrates radiomics analysis for enhanced per...

An imaging-based artificial intelligence model for non-invasive grading of hepatic venous pressure gradient in cirrhotic portal hypertension.

The hepatic venous pressure gradient (HVPG) is the gold standard for cirrhotic portal hypertension (...

Application of Deep Learning Techniques for Automated Diagnosis of Non-Syndromic Craniosynostosis Using Skull.

Non-syndromic craniosynostosis (NSCS) is a disease, in which a single cranial bone suture is prematu...

Enhancing Detection Quality Rate with a Combined HOG and CNN for Real-Time Multiple Object Tracking across Non-Overlapping Multiple Cameras.

Multi-object tracking in video surveillance is subjected to illumination variation, blurring, motion...

An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions.

OBJECTIVES: To build an artificial intelligence (AI) system to classify benign and malignant non-mas...