Pneumonia

Generative deep learning for macromolecular structure and dynamics.

Much scientific enquiry across disciplines is founded upon a mechanistic treatment of dynamic systems that ties form to function. A highly visible instance of this is in molecular biology, where characterizing macromolecular structure and dynamics is central to a detailed, molecular-level understanding of biological processes in the living cell. The current computational paradigm utilizes optimiza...

Cellpose: a generalist algorithm for cellular segmentation.

Many biological applications require the segmentation of cell bodies, membranes and nuclei from microscopy images. Deep learning has enabled great progress on this problem, but current methods are specialized for images that have large training datasets. Here we introduce a generalist, deep learning-based segmentation method called Cellpose, which can precisely segment cells from a wide range of i...

KGen: a knowledge graph generator from biomedical scientific literature.

BACKGROUND: Knowledge is often produced from data generated in scientific investigations. An ever-growing number of scientific studies in several doma...

Artificial Intelligence Applied to Chest X-Ray Images for the Automatic Detection of COVID-19. A Thoughtful Evaluation Approach.

Current standard protocols used in the clinic for diagnosing COVID-19 include molecular or antigen tests, generally complemented by a plain chest X-Ra...

Hybrid-COVID: a novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray images.

The novel Coronavirus disease (COVID-19), which first appeared at the end of December 2019, continues to spread rapidly in most countries of the world...

Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels.

Early and accurate diagnosis of Coronavirus disease (COVID-19) is essential for patient isolation and contact tracing so that the spread of infection ...

M Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening From CT Imaging.

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preve...

StackNet-DenVIS: a multi-layer perceptron stacked ensembling approach for COVID-19 detection using X-ray images.

The highly contagious nature of Coronavirus disease 2019 (Covid-19) resulted in a global pandemic. Due to the relatively slow and taxing nature of con...

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning.

Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in...

"Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images".

Coronavirus disease 2019 (COVID-19) is a novel harmful respiratory disease that has rapidly spread worldwide. At the end of 2019, COVID-19 emerged as ...

The Potential of Artificial Intelligence to Analyze Chest Radiographs for Signs of COVID-19 Pneumonia.

Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools.

The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune res...

Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study.

The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image in...

The ImageJ ecosystem: Open-source software for image visualization, processing, and analysis.

For decades, biologists have relied on software to visualize and interpret imaging data. As techniques for acquiring images increase in complexity, re...

Learning Bayesian networks from demographic and health survey data.

Child mortality from preventable diseases such as pneumonia and diarrhoea in low and middle-income countries remains a serious global challenge. We co...

Deep learning to predict elevated pulmonary artery pressure in patients with suspected pulmonary hypertension using standard chest X ray.

Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of art...

FaNet: fast assessment network for the novel coronavirus (COVID-19) pneumonia based on 3D CT imaging and clinical symptoms.

The novel coronavirus (COVID-19) pneumonia has become a serious health challenge in countries worldwide. Many radiological findings have shown that X-...

Machine learning in predicting respiratory failure in patients with COVID-19 pneumonia-Challenges, strengths, and opportunities in a global health emergency.

AIMS: The aim of this study was to estimate a 48 hour prediction of moderate to severe respiratory failure, requiring mechanical ventilation, in hospi...

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images.

The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. A criti...

Deep neural network to detect COVID-19: one architecture for both CT Scans and Chest X-rays.

Since December 2019, the novel COVID-19's spread rate is exponential, and AI-driven tools are used to prevent further spreading [1]. They can help pre...