Pneumonia

Multitask Adversarial Networks Based on Extensive Nonlinear Spiking Neuron Models.

Deep learning technology has been successfully used in Chest X-ray (CXR) images of COVID-19 patients. However, due to the characteristics of COVID-19 pneumonia and X-ray imaging, the deep learning methods still face many challenges, such as lower imaging quality, fewer training samples, complex radiological features and irregular shapes. To address these challenges, this study first introduces an ...

CovMediScanX: A medical imaging solution for COVID-19 diagnosis from chest X-ray images.

INTRODUCTION: Radiologists have extensively employed the interpretation of chest X-rays (CXR) to identify visual markers indicative of COVID-19 infection, offering an alternative approach for the screening of infected individuals. This research article presents CovMediScanX, a deep learning-based framework designed for a rapid and automated diagnosis of COVID-19 from CXR scan images.

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec.

Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (...

Automatic ARDS surveillance with chest X-ray recognition using convolutional neural networks.

OBJECTIVE: This study aims to design, validate and assess the accuracy a deep learning model capable of differentiation Chest X-Rays between pneumonia...

Reverse engineering protection: A comprehensive survey of reverse vaccinology-based vaccines targeting viral pathogens.

Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine developme...

Using metabolic networks to predict cross-feeding and competition interactions between microorganisms.

Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbi...

STELA: a community-centred approach to norm elicitation for AI alignment.

Value alignment, the process of ensuring that artificial intelligence (AI) systems are aligned with human values and goals, is a critical issue in AI ...

Enhancing pediatric pneumonia diagnosis through masked autoencoders.

Pneumonia, an inflammatory lung condition primarily triggered by bacteria, viruses, or fungi, presents distinctive challenges in pediatric cases due t...

Multi-modal deep learning methods for classification of chest diseases using different medical imaging and cough sounds.

Chest disease refers to a wide range of conditions affecting the lungs, such as COVID-19, lung cancer (LC), consolidation lung (COL), and many more. W...

Evaluation of Effectiveness of Self-Supervised Learning in Chest X-Ray Imaging to Reduce Annotated Images.

A significant challenge in machine learning-based medical image analysis is the scarcity of medical images. Obtaining a large number of labeled medica...

Of editorial processes, AI models, and medical literature: the Magnetic Resonance Audiometry experiment.

The potential of artificial intelligence (AI) in the field of medical research is unquestionable. Nevertheless, the scientific community has raised se...

Machine learning models for the early prediction of ventilator-associated pneumonia: Author's reply.

Construction of an aerolysin-based multi-epitope vaccine against an machine learning and artificial intelligence-supported approach.

, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroe...

CODENET: A deep learning model for COVID-19 detection.

Conventional COVID-19 testing methods have some flaws: they are expensive and time-consuming. Chest X-ray (CXR) diagnostic approaches can alleviate th...

PulmoNet: a novel deep learning based pulmonary diseases detection model.

Pulmonary diseases are various pathological conditions that affect respiratory tissues and organs, making the exchange of gas challenging for animals ...

Artificial intelligence-based model for predicting pulmonary arterial hypertension on chest x-ray images.

BACKGROUND: Pulmonary arterial hypertension is a serious medical condition. However, the condition is often misdiagnosed or a rather long delay occurs...

Improving Access to Eye Care Through Community Health Screenings Using Artificial Intelligence.

PURPOSE: To the best of our knowledge, implementation of artificial intelligence (AI)-based vision screening in community health fair settings has not...

Raman spectrum combined with deep learning for precise recognition of Carbapenem-resistant Enterobacteriaceae.

Carbapenem-resistant Enterobacteriaceae (CRE) is a major pathogen that poses a serious threat to human health. Unfortunately, currently, there are no ...

Machine learning-based prediction of vitamin D deficiency: NHANES 2001-2018.

BACKGROUND: Vitamin D deficiency is strongly associated with the development of several diseases. In the current context of a global pandemic of vitam...

Immunization against inhibin DNA vaccine as an alternative therapeutic for improving follicle development and reproductive performance in beef cattle.

The objective of the present study was to investigate the potential role of immunization against INH on follicular development, serum reproductive hor...