Infectious Disease

COVID-19

Latest AI and machine learning research in covid-19 for healthcare professionals.

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A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.

IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a ...

Pretrainable geometric graph neural network for antibody affinity maturation.

Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody t...

A machine learning approach for rapid early detection of Campylobacter spp. using absorbance spectra collected from enrichment cultures.

Enumeration of Campylobacter from environmental waters can be difficult due to its low concentration...

A Joint Classification Method for COVID-19 Lesions Based on Deep Learning and Radiomics.

Pneumonia caused by novel coronavirus is an acute respiratory infectious disease. Its rapid spread i...

A Physics-Informed Neural Network approach for compartmental epidemiological models.

Compartmental models provide simple and efficient tools to analyze the relevant transmission process...

Internal Medicine Year in Review 2023.

The year 2023 marked a significant change for Internal Medicine, as the number of submissions relate...

Brain tumor image segmentation method using hybrid attention module and improved mask RCNN.

To meet the needs of automated medical analysis of brain tumor magnetic resonance imaging, this stud...

Leveraging Supervised Machine Learning Algorithms for System Suitability Testing of Mass Spectrometry Imaging Platforms.

Quality control and system suitability testing are vital protocols implemented to ensure the repeata...

Deep graph representation learning for influence maximization with accelerated inference.

Selecting a set of initial users from a social network in order to maximize the envisaged number of ...

From code sharing to sharing of implementations: Advancing reproducible AI development for medical imaging through federated testing.

BACKGROUND: The reproducibility crisis in AI research remains a significant concern. While code shar...

A deep convolutional neural network approach using medical image classification.

The epidemic diseases such as COVID-19 are rapidly spreading all around the world. The diagnosis of ...

CNVDeep: deep association of copy number variants with neurocognitive disorders.

BACKGROUND: Copy number variants (CNVs) have become increasingly instrumental in understanding the e...

Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability.

Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activ...

Constraint based Bayesian optimization of bioink precursor: a machine learning framework.

Current research practice for optimizing bioink involves exhaustive experimentation with multi-mater...

COVID-19 severity detection using chest X-ray segmentation and deep learning.

COVID-19 has resulted in a significant global impact on health, the economy, education, and daily li...

Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound.

BACKGROUND AND OBJECTIVES: Severe pneumonia is the leading cause of death among young children world...

The impacts of positive selection on genomic variation in Drosophila serrata: Insights from a deep learning approach.

This study explores the impact of positive selection on the genetic composition of a Drosophila serr...

Long COVID diagnostic with differentiation from chronic lyme disease using machine learning and cytokine hubs.

The absence of a long COVID (LC) or post-acute sequelae of COVID-19 (PASC) diagnostic has profound i...

Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer's disease.

Alzheimer's disease (AD) involves aggregation of amyloid β and tau, neuron loss, cognitive decline, ...

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