Pneumonia

Transition from sulfur autotrophic to mixotrophic denitrification: Performance with different carbon sources, microbial community and artificial neural network modeling.

To address the limitations inherent in both sulfur autotrophic denitrification (SAD) and heterotrophic denitrification (HD) processes, this study introduces a novel approach. Three carbon sources (glucose, methanol, and sodium acetate) were fed into the SAD system to facilitate the transition towards mixotrophic denitrification. Batch experiments were conducted to explore the effects of influencin...

COVID-19 vaccinations and their side effects: a scoping systematic review.

The COVID-19 virus has impacted people worldwide, causing significant changes in their lifestyles. Since the emergence of the epidemic, attempts have begun to prepare a vaccine that can eliminate the virus and restore balance to life in the entire world. Over the past two years, countries and specialized companies have competed to obtain a license from the World Health Organization for the vaccin...

Radiograph accelerated detection and identification of cancer in the lung (RADICAL): a mixed methods study to assess the clinical effectiveness and acceptability of Qure.ai artificial intelligence software to prioritise chest X-ray (CXR) interpretation.

INTRODUCTION: Diagnosing and treating lung cancer in early stages is essential for survival outcomes. The chest X-ray (CXR) remains the primary screen...

The Potential Clinical Utility of an Artificial Intelligence Model for Identification of Vertebral Compression Fractures in Chest Radiographs.

PURPOSE: To assess the ability of the Annalise Enterprise CXR Triage Trauma (Annalise AI Pty Ltd, Sydney, NSW, Australia) artificial intelligence mode...

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control.

Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices...

Applying a community-engaged participatory machine learning model.

Although predictive algorithms have been described as the definitive solution to bias in health care, machine learning techniques may also propagate e...

Screening Patient Misidentification Errors Using a Deep Learning Model of Chest Radiography: A Seven Reader Study.

We aimed to evaluate the ability of deep learning (DL) models to identify patients from a paired chest radiograph (CXR) and compare their performance ...

CONSTRUCTING A DIAGNOSTIC PREDICTION MODEL TO ESTIMATE THE SEVERE RESPIRATORY SYNCYTIAL VIRUS PNEUMONIA IN CHILDREN BASED ON MACHINE LEARNING.

Background : Severe respiratory syncytial virus (RSV) pneumonia is a leading cause of hospitalization and morbidity in infants and young children. Ear...

Artificial intelligence-based quantification of pulmonary HRCT (AIqpHRCT) for the evaluation of interstitial lung disease in patients with inflammatory rheumatic diseases.

High-resolution computed tomography (HRCT) is important for diagnosing interstitial lung disease (ILD) in inflammatory rheumatic disease (IRD) patient...

The Role of Complicated Grief in Health Inequities in American Indian Communities.

Complicated grief is both a cause and a consequence of health inequities in Native (American Indian/Alaska Native [AI/AN]) communities. Given dispropo...

A Joint Classification Method for COVID-19 Lesions Based on Deep Learning and Radiomics.

Pneumonia caused by novel coronavirus is an acute respiratory infectious disease. Its rapid spread in a short period of time has brought great challen...

Improving viral annotation with artificial intelligence.

Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their depend...

Fuzzy lattices assisted EJAYA Q-learning for automated pulmonary diseases classification.

This work proposes a novel technique called Enhanced JAYA (EJAYA) assisted Q-Learning for the classification of pulmonary diseases, such as pneumonia ...

Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features.

The use of artificial intelligence (AI) in high-resolution computed tomography (HRCT) for diagnosing systemic sclerosis-associated interstitial lung d...

Advancing Chinese biomedical text mining with community challenges.

OBJECTIVE: This study aims to review the recent advances in community challenges for biomedical text mining in China.

Deep Learning-Based System Combining Chest X-Ray and Computerized Tomography Images for COVID-19 Diagnosis.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for accurate and efficient diagnostic methods. This study aims to improve C...

COVID-19 severity detection using chest X-ray segmentation and deep learning.

COVID-19 has resulted in a significant global impact on health, the economy, education, and daily life. The disease can range from mild to severe, wit...

Development and testing of a deep learning algorithm to detect lung consolidation among children with pneumonia using hand-held ultrasound.

BACKGROUND AND OBJECTIVES: Severe pneumonia is the leading cause of death among young children worldwide, disproportionately impacting children who la...

Development and Testing of Artificial Intelligence-Based Mobile Application to Achieve Cataract Backlog-Free Status in Uttar Pradesh, India.

BACKGROUND: Uttar Pradesh (UP), the most populous state in India, has about 36 million people aged 50 years or older, spread across more than 100,000 ...

Factors for increasing positive predictive value of pneumothorax detection on chest radiographs using artificial intelligence.

This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its...