Infectious Disease

Latest AI and machine learning research in infectious disease for healthcare professionals.

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Deep neural networks excel in COVID-19 disease severity prediction-a meta-regression analysis.

COVID-19 is a disease in which early prognosis of severity is critical for desired patient outcomes ...

Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.

Continuous high-resolution imaging of the disease-mediating blood stages of the human malaria parasi...

Enhanced diagnosis of multi-drug-resistant microbes using group association modeling and machine learning.

New solutions are needed to detect genotype-phenotype associations involved in microbial drug resist...

Point-of-Care Sensors and Medical Internet-of-Things Technologies to Manage Catheter-Associated Urinary Tract Infections in the Intensive Care Unit.

This article examines the current technologies used with indwelling urinary catheters to monitor pot...

Application of explainable machine learning in the production of pullulan by Aureobasidium pullulans CGMCCNO.7055.

The application of machine learning in pullulan biofermentation has demonstrated significant potenti...

Enhanced tuberculosis detection using Vision Transformers and explainable AI with a Grad-CAM approach on chest X-rays.

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a leading global health challenge, ...

Weighted-VAE: A deep learning approach for multimodal data generation applied to experimental T. cruzi infection.

Chagas disease (CD), caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), represents a maj...

Leveraging artificial intelligence to assess the impact of COVID-19 on the teacher-student relationship in higher education.

The teacher-student relationship has far-reaching implications for educational outcomes at the terti...

TCDE-Net: An unsupervised dual-encoder network for 3D brain medical image registration.

Medical image registration is a critical task in aligning medical images from different time points,...

Artificial intelligence-assisted magnetic resonance lymphography for evaluation of micro- and macro-sentinel lymph node metastasis in breast cancer.

Contrast-enhanced magnetic resonance lymphography (CE-MRL) plays a crucial role in preoperative diag...

Infection and Inflammation in Nuclear Medicine Imaging: The Role of Artificial Intelligence.

Infectious and inflammatory diseases represent a global challenge. Delayed diagnosis and treatment l...

Machine learning-based model for predicting all-cause mortality in severe pneumonia.

BACKGROUND: Severe pneumonia has a poor prognosis and high mortality. Current severity scores such a...

Machine learning-based prediction of vesicoureteral reflux outcomes in infants under antibiotic prophylaxis.

We aimed to investigate the independent outcome predictors of continuous antibiotic prophylaxis (CAP...

Explainable SHAP-XGBoost models for pressure injuries among patients requiring with mechanical ventilation in intensive care unit.

pressure injuries are significant concern for ICU patients on mechanical ventilation. Early predicti...

Systems biology of Haemonchus contortus - Advancing biotechnology for parasitic nematode control.

Parasitic nematodes represent a substantial global burden, impacting animal health, agriculture and ...

Assessment for antibiotic resistance in : A practical and interpretable machine learning model based on genome-wide genetic variation.

() antibiotic resistance poses a global health threat. Accurate identification of antibiotic resist...

Forewarning the seasonal dynamics of corn leafhopper and mollicutes through neural networks.

The corn leafhopper (CL), Dalbulus maidis (DeLong & Wolcott) (Hemiptera: Cicadellidae), has become t...

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