Hematology

Lymphoma

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

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Enhancing classification of active and non-active lesions in multiple sclerosis: machine learning models and feature selection techniques.

INTRODUCTION: Gadolinium-based T1-weighted MRI sequence is the gold standard for the detection of ac...

Deep learning-based intratumoral and peritumoral features for differentiating ocular adnexal lymphoma and idiopathic orbital inflammation.

OBJECTIVES: To evaluate the value of deep-learning-based intratumoral and peritumoral features for d...

Evaluation of hypoxia-inducible factor-1α and urine non-transferrin-bound iron concentrations in cats with chronic kidney disease.

INTRODUCTION: Hypoxia-inducible factors (HIF) regulate gene transcription, which aids hypoxia adapta...

Deep learning detected histological differences between invasive and non-invasive areas of early esophageal cancer.

The depth of invasion plays a critical role in predicting the prognosis of early esophageal cancer, ...

Radiomics and deep learning features of pericoronary adipose tissue on non-contrast computerized tomography for predicting non-calcified plaques.

BACKGROUND: Inflammation of coronary arterial plaque is considered a key factor in the development o...

Recognizing SARS-CoV-2 infection of nasopharyngeal tissue at the single-cell level by machine learning method.

SARS-CoV-2 has posed serious global health challenges not only because of the high degree of virus t...

Lymphoma triage from H&E using AI for improved clinical management.

AIMS: In routine diagnosis of lymphoma, initial non-specialist triage is carried out when the sample...

Combination Therapy with Baricitinib and Narrowband Ultraviolet B for Active Non-Segmental Vitiligo: A Retrospective Controlled Study.

BACKGROUND: Vitiligo is a chronic autoimmune disease manifested by depigmented patches of skin devoi...

A non-local dual-stream fusion network for laryngoscope recognition.

PURPOSE: To use deep learning technology to design and implement a model that can automatically clas...

Passivity and robust passivity of inertial memristive neural networks with time-varying delays via non-reduced order method.

This study examines the concepts of passivity and robust passivity in inertial memristive neural net...

Assessment of body composition and prediction of infectious pancreatic necrosis via non-contrast CT radiomics and deep learning.

AIM: The current study aims to delineate subcutaneous adipose tissue (SAT), visceral adipose tissue ...

Hybrid SEM-ANN model for predicting undergraduates' e-learning continuance intention based on perceived educational and emotional support.

Based on the Expectation Confirmation Model (ECM), this study explores the impact of perceived educa...

BUSClean: Open-source software for breast ultrasound image pre-processing and knowledge extraction for medical AI.

Development of artificial intelligence (AI) for medical imaging demands curation and cleaning of lar...

Enhancing automatic sleep stage classification with cerebellar EEG and machine learning techniques.

Sleep disorders have become a significant health concern in modern society. To investigate and diagn...

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