Hematology

Lymphoma

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

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Machine learning-based analysis of Ga-PSMA-11 PET/CT images for estimation of prostate tumor grade.

Early diagnosis of prostate cancer, the most common malignancy in men, can improve patient outcomes....

BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification.

The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding g...

Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation,...

Machine learning models for classifying non-specific neck pain using craniocervical posture and movement.

OBJECTIVE: Physical therapists and clinicians commonly confirm craniocervical posture (CCP), cervica...

Application of MALDI-TOF MS and machine learning for the detection of SARS-CoV-2 and non-SARS-CoV-2 respiratory infections.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could ai...

Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets.

Machine vision systems have emerged for quality assessment of solid dosage forms in the pharmaceutic...

Enhancing compound confidence in suspect and non-target screening through machine learning-based retention time prediction.

The retention time (RT) of contaminants of emerging concern (CECs) in liquid chromatography-high-res...

Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images.

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improv...

An accurately supervised motion-aware deep network for non-contact pain assessment of trigeminal neuralgia mouse model.

Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysio...

Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence.

BACKGROUND: Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, affecting people wi...

Enabling large-scale screening of Barrett's esophagus using weakly supervised deep learning in histopathology.

Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal adenocarcinoma, c...

Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other h...

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