Rheumatology

Lupus

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

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Hyb_SEnc: An Antituberculosis Peptide Predictor Based on a Hybrid Feature Vector and Stacked Ensemble Learning.

Tuberculosis has plagued mankind since ancient times, and the struggle between humans and tuberculos...

Machine Learning-Assisted High-Throughput Screening for Anti-MRSA Compounds.

BACKGROUND: Antimicrobial resistance is a major public health threat, and new agents are needed. Com...

Generative Adversarial Network-Based Augmentation With Noval 2-Step Authentication for Anti-Coronavirus Peptide Prediction.

The virus poses a longstanding and enduring danger to various forms of life. Despite the ongoing end...

The isolation, bioactivity, and synthesis of natural products from with anti-HIV activities.

Natural products isolated from have attracted considerable attention from the chemical community du...

Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.

BACKGROUND: Efforts toward tuberculosis management and control are challenged by the emergence of My...

anti-cancer activity of siddha metallo-mineral formulation from Thanga uram with Hela cell lines.

The second most common malignant tumour in women worldwide, cervical cancer seriously jeopardizes th...

Automatic classification of HEp-2 specimens by explainable deep learning and Jensen-Shannon reliability index.

The Anti-Nuclear Antibodies (ANA) test using Human Epithelial type 2 (HEp-2) cells in the Indirect I...

A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds.

Identifying new compounds with minimal side effects to enhance patients' quality of life is the ulti...

Rough hypervolume-driven feature selection with groupwise intelligent sampling for detecting clinical characterization of lupus nephritis.

Systemic lupus erythematosus (SLE) is an autoimmune inflammatory disease. Lupus nephritis (LN) is a ...

RS-MOCO: A deep learning-based topology-preserving image registration method for cardiac T1 mapping.

Cardiac T1 mapping can evaluate various clinical symptoms of myocardial tissue. However, there is cu...

Leveraging AI models for lesion detection in osteonecrosis of the femoral head and T1-weighted MRI generation from radiographs.

This study emphasizes the importance of early detection of osteonecrosis of the femoral head (ONFH) ...

Improved facial emotion recognition model based on a novel deep convolutional structure.

Facial Emotion Recognition (FER) is a very challenging task due to the varying nature of facial expr...

A Multi-task learning U-Net model for end-to-end HEp-2 cell image analysis.

Antinuclear Antibody (ANA) testing is pivotal to help diagnose patients with a suspected autoimmune ...

Machine learning identifies cytokine signatures of disease severity and autoantibody profiles in systemic lupus erythematosus - a pilot study.

Disrupted cytokine networks and autoantibodies play an important role in the pathogenesis of systemi...

Machine learning identifies immune-based biomarkers that predict efficacy of anti-angiogenesis-based therapies in advanced lung cancer.

BACKGROUND: The anti-angiogenic drugs showed remarkable efficacy in the treatment of lung cancer. No...

Learning to predict perceptual visibility of rendering deterioration in computer games.

Contemporary computer gaming affords players the agency to manually tailor rendering settings, a cap...

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