Pneumonia

Development and Feasibility Pilot Study of Indigenous Recovery Planning: A Community-Engaged Approach to Addressing Substance Use in a Native Community.

Although Native (American Indian and Alaska Native [AI/AN]) populations have high rates of abstinence from alcohol, health problems associated with substance use remain a pressing concern in many AI/AN communities. As part of a longstanding community-based participatory research (CBPR) project involving five years of relationship building and three preliminary studies, our team of academic and com...

Prediction of cooling effect of constant temperature community bin based on BP neural network.

In order to explore the influence of outdoor microclimate on the cooling effect of constant temperature community bin, the temperature prediction model was predicted. The temperature and microclimate data sets of the community bin were collected in summer from May 2021 to September 2021. The climatic characteristics included cloudy and sunny conditions, and the environmental factors included outdo...

CXR-Net: A Multitask Deep Learning Network for Explainable and Accurate Diagnosis of COVID-19 Pneumonia From Chest X-Ray Images.

Accurate and rapid detection of COVID-19 pneumonia is crucial for optimal patient treatment. Chest X-Ray (CXR) is the first-line imaging technique for...

Lung Diseases Detection Using Various Deep Learning Algorithms.

The primary objective of this proposed framework work is to detect and classify various lung diseases such as pneumonia, tuberculosis, and lung cancer...

Comparison of Chest Radiograph Captions Based on Natural Language Processing vs Completed by Radiologists.

IMPORTANCE: Artificial intelligence (AI) can interpret abnormal signs in chest radiography (CXR) and generate captions, but a prospective study is nee...

PneuNet: deep learning for COVID-19 pneumonia diagnosis on chest X-ray image analysis using Vision Transformer.

A long-standing challenge in pneumonia diagnosis is recognizing the pathological lung texture, especially the ground-glass appearance pathological tex...

A survey of machine learning-based methods for COVID-19 medical image analysis.

The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected aft...

Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases.

Chronic obstructive pulmonary disease (COPD) concerns the serious decline of human lung functions. These have emerged as one of the most concerning he...

CNN-RNN Network Integration for the Diagnosis of COVID-19 Using Chest X-ray and CT Images.

The 2019 coronavirus disease (COVID-19) has rapidly spread across the globe. It is crucial to identify positive cases as rapidly as humanely possible ...

COVID-19 Classification on Chest X-ray Images Using Deep Learning Methods.

Since December 2019, the coronavirus disease has significantly affected millions of people. Given the effect this disease has on the pulmonary systems...

Comparison of the Diagnostic Performance of Deep Learning Algorithms for Reducing the Time Required for COVID-19 RT-PCR Testing.

(1) Background: Rapid and accurate negative discrimination enables efficient management of scarce isolated bed resources and adequate patient accommod...

Racial Health Disparities and Black Heterogeneity in COVID-19: A Case Study of Miami Gardens.

The COVID-19 pandemic is a critical public health concern that has disproportionately affected the Black community in the United States. The purpose o...

An application of deep dual convolutional neural network for enhanced medical image denoising.

This work investigates the medical image denoising (MID) application of the dual denoising network (DudeNet) model for chest X-ray (CXR). The DudeNet ...

Coronavirus covid-19 detection by means of explainable deep learning.

The coronavirus is caused by the infection of the SARS-CoV-2 virus: it represents a complex and new condition, considering that until the end of Decem...

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-...

A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.

The novel coronavirus pneumonia that began to spread in 2019 is still raging and has placed a burden on medical systems and governments in various cou...

Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processing.

Pre-processing is widely applied in medical image analysis to remove the interference information. However, the existing pre-processing solutions main...

Evolutionary game analysis of community elderly care service regulation in the context of "Internet +".

BACKGROUND: As an upgraded form of the elderly care service industry, "Internet + Community Elderly Care" integrates information technology, artificia...

Reducing Errors Resulting From Commonly Missed Chest Radiography Findings.

Chest radiography (CXR), the most frequently performed imaging examination, is vulnerable to interpretation errors resulting from commonly missed find...

Sports Video Classification Framework Using Enhanced Threshold Based Keyframe Selection Algorithm and Customized CNN on UCF101 and Sports1-M Dataset.

The computer vision community has taken a keen interest in recent developments in activity recognition and classification in sports videos. Advancemen...