Infectious Disease

COVID-19

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

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Mask R-CNN based multiclass segmentation model for endotracheal intubation using video laryngoscope.

OBJECTIVE: Endotracheal intubation (ETI) is critical to secure the airway in emergent situations. Al...

Leveraging attention-enhanced variational autoencoders: Novel approach for investigating latent space of aptamer sequences.

Aptamers are increasingly recognized as potent alternatives to antibodies for diagnostic and therape...

Towards fully automated inner ear analysis with deep-learning-based joint segmentation and landmark detection framework.

Automated analysis of the inner ear anatomy in radiological data instead of time-consuming manual as...

Plant disease identification using contextual mask auto-encoder optimized with dynamic differential annealed optimization algorithm.

Most of the food consumed worldwide is produced by plants. Plant disease is a major cause of reduced...

Automated Deep Learning-Based Diagnosis and Molecular Characterization of Acute Myeloid Leukemia Using Flow Cytometry.

The current flow cytometric analysis of blood and bone marrow samples for diagnosis of acute myeloid...

How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images.

Over the past decade, the use of deep learning has been widely increasing in the medical image diagn...

Predicting multiple linear stapler firings in double stapling technique with an MRI-based deep-learning model.

Multiple linear stapler firings is a risk factor for anastomotic leakage (AL) in laparoscopic low an...

Mapping the flow of knowledge as guidance for ethics implementation in medical AI: A qualitative study.

In response to the COVID-19 crisis, Artificial Intelligence (AI) has been applied to a range of appl...

Preclinical efficacy of a cell division protein candidate gonococcal vaccine identified by artificial intelligence.

Vaccines to curb the global spread of multidrug-resistant gonorrhea are urgently needed. Here, 26 va...

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.

The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextensio...

Digenic Analysis Finds Highly Interactive Genetic Variants Underlying Polygenic Traits.

We briefly review our recently published approach to mining digenic genotype patterns, which consist...

Reservoir computing models based on spiking neural P systems for time series classification.

Nonlinear spiking neural P (NSNP) systems are neural-like membrane computing models with nonlinear s...

Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era.

Recently, fundus photography (FP) is being increasingly used. Corneal curvature is an essential fact...

FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation.

The increase of available large clinical and experimental datasets has contributed to a substantial ...

A White-Box Testing for Deep Neural Networks Based on Neuron Coverage.

With the introduction of neuron coverage as a testing criterion for deep neural networks (DNNs), cov...

Integrated Molecular Modeling and Machine Learning for Drug Design.

Modern therapeutic development often involves several stages that are interconnected, and multiple i...

Evorpacept-Induced Interference and Application of a Novel Mitigation Agent, Evo-NR, in Pretransfusion Testing.

INTRODUCTION: Evorpacept is a CD47-blocking agent currently being developed for the treatment of var...

IoMT based smart healthcare system to control outbreaks of the COVID-19 pandemic.

The COVID-19 pandemic caused millions of infections and deaths globally requiring effective solution...

Estimation of right lobe graft weight for living donor liver transplantation using deep learning-based fully automatic computed tomographic volumetry.

This study aimed at developing a fully automatic technique for right lobe graft weight estimation us...

MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites.

Malaria remains one of the deadliest infectious diseases. Transcriptional regulation effects of nonc...

Application of multiple-finding segmentation utilizing Mask R-CNN-based deep learning in a rat model of drug-induced liver injury.

Drug-induced liver injury (DILI) presents significant diagnostic challenges, and recently artificial...

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