Infectious Disease

COVID-19

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

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Transfer Learning for COVID-19 cases and deaths forecast using LSTM network.

In this paper, Transfer Learning is used in LSTM networks to forecast new COVID cases and deaths. Mo...

Machine learning models for wetland habitat vulnerability in mature Ganges delta.

The present study attempts to measure wetland habitat vulnerability (WHV) in the Indian part of matu...

Retraining Convolutional Neural Networks for Specialized Cardiovascular Imaging Tasks: Lessons from Tetralogy of Fallot.

Ventricular contouring of cardiac magnetic resonance imaging is the gold standard for volumetric ana...

Fast automated detection of COVID-19 from medical images using convolutional neural networks.

Coronavirus disease 2019 (COVID-19) is a global pandemic posing significant health risks. The diagno...

Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit.

Traditional Machine Learning (ML) models have had limited success in predicting Coronoavirus-19 (COV...

The role of quantitative HBsAg in the natural history of e antigen-negative chronic hepatitis B: A Tunisian prospective study.

BACKGROUND/AIMS: During the natural course of Chronic Hepatitis B (CHB) infection, differentiation b...

The usage of deep neural network improves distinguishing COVID-19 from other suspected viral pneumonia by clinicians on chest CT: a real-world study.

OBJECTIVES: Based on the current clinical routine, we aimed to develop a novel deep learning model t...

Role of the Health System in Combating Covid-19: Cross-Section Analysis and Artificial Neural Network Simulation for 124 Country Cases.

In the fight against Covid-19, developed countries and developing countries diverge in success. This...

Design of novel orotransmucosal vaccine-delivery platforms using artificial intelligence.

The linings of the oral cavity are excellent needle-free vaccination sites, able to induce immune re...

Characterization of Antiphospholipid Syndrome Atherothrombotic Risk by Unsupervised Integrated Transcriptomic Analyses.

OBJECTIVE: Our aim was to characterize distinctive clinical antiphospholipid syndrome phenotypes and...

Lightweight deep learning models for detecting COVID-19 from chest X-ray images.

Deep learning methods have already enjoyed an unprecedented success in medical imaging problems. Sim...

Segmentation of COVID-19 pneumonia lesions: A deep learning approach.

Lung CT scan has a pivotal role in diagnosis and monitoring of COVID-19 patients, and with growing ...

Tactile Model O: Fabrication and Testing of a 3D-Printed, Three-Fingered Tactile Robot Hand.

Bringing tactile sensation to robotic hands will allow for more effective grasping, along with a wid...

Machine Learning Feature Selection for Predicting High Concentration Therapeutic Antibody Aggregation.

Protein aggregation can hinder the development, safety and efficacy of therapeutic antibody-based dr...

Deep learning-based real-time volumetric imaging for lung stereotactic body radiation therapy: a proof of concept study.

Due to the inter- and intra- variation of respiratory motion, it is highly desired to provide real-t...

Active contour regularized semi-supervised learning for COVID-19 CT infection segmentation with limited annotations.

Infection segmentation on chest CT plays an important role in the quantitative analysis of COVID-19....

Development and Prospective Validation of a Deep Learning Algorithm for Predicting Need for Mechanical Ventilation.

BACKGROUND: Objective and early identification of hospitalized patients, and particularly those with...

Deep-learning-based three-dimensional label-free tracking and analysis of immunological synapses of CAR-T cells.

The immunological synapse (IS) is a cell-cell junction between a T cell and a professional antigen-p...

Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks.

Owing the epidemic of the novel coronavirus disease 2019 (COVID-19), chest X-ray computed tomography...

Semi-automatic sigmoid colon segmentation in CT for radiation therapy treatment planning via an iterative 2.5-D deep learning approach.

Automatic sigmoid colon segmentation in CT for radiotherapy treatment planning is challenging due to...

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