Pneumonia

Integrating multiple spatial transcriptomics data using community-enhanced graph contrastive learning.

Due to the rapid development of spatial sequencing technologies, large amounts of spatial transcriptomic datasets have been generated across various technological platforms or different biological conditions (e.g., control vs. treatment). Spatial transcriptomics data coming from different platforms usually has different resolutions. Moreover, current methods do not consider the heterogeneity of sp...

Performance of Computer-Aided Detection Software in Tuberculosis Case Finding in Township Health Centers in China.

BACKGROUND: Computer-aided detection (CAD) software has been introduced to automatically interpret digital chest X-rays. This study aimed to evaluate the performance of CAD software (JF CXR-1 v3.0, which was developed by a domestic Hi-tech enterprise) in tuberculosis (TB) case finding in China.

Effectiveness of a community intervention program on healthy lifestyles (PREDICOL) among adults with prediabetes in two Latin American cities: A quasi-experimental study.

PURPOSE: This study aimed to measure the impact of a community-based lifestyle modification intervention program on the Health-Related Quality of Life...

Real-Time American Sign Language Interpretation Using Deep Learning and Keypoint Tracking.

Communication barriers pose significant challenges for the Deaf and Hard-of-Hearing (DHH) community, limiting their access to essential services, soci...

Machine learning prediction models for multidrug-resistant organism infections in ICU ventilator-associated pneumonia patients: Analysis using the MIMIC-IV database.

OBJECTIVE: This study aims to construct and compare four machine learning models using the MIMIC-IV database to identify high-risk factors for multidr...

Preliminary evaluation of ChatGPT model iterations in emergency department diagnostics.

Large language model chatbots such as ChatGPT have shown the potential in assisting health professionals in emergency departments (EDs). However, the ...

Who Tweets for the autistic community? A natural language processing-driven investigation.

The formation of autism advocacy organisations led by family members of autistic individuals led to intense criticism from some parts of the autistic ...

Machine learning-based model for predicting all-cause mortality in severe pneumonia.

BACKGROUND: Severe pneumonia has a poor prognosis and high mortality. Current severity scores such as Acute Physiology and Chronic Health Evaluation (...

Performance evaluation of reduced complexity deep neural networks.

Deep Neural Networks (DNN) have achieved state-of-the-art performance in medical image classification and are increasingly being used for disease diag...

Development of machine learning-based differential diagnosis model and risk prediction model of organ damage for severe Mycoplasma pneumoniae pneumonia in children.

Severe Mycoplasma pneumoniae pneumonia (SMPP) poses significant diagnostic challenges due to its clinical features overlapping with those of other com...

User-Centered Prototype Design of a Health Care Robot for Treating Type 2 Diabetes in the Community Pharmacy: Development and Usability Study.

BACKGROUND: Technology can be an effective tool for providing health services and disease self-management, especially in diabetes care. Technology too...

Enhancing Relation Extraction for COVID-19 Vaccine Shot-Adverse Event Associations with Large Language Models.

OBJECTIVE: The rapid evolution of the COVID-19 virus has led to the development of different vaccine shots, each designed to combat specific variants ...

LHR-RFL: Linear Hybrid-Reward-Based Reinforced Focal Learning for Automatic Radiology Report Generation.

Radiology report generation that aims to accurately describe medical findings for given images, is pivotal in contemporary computer-aided diagnosis. R...

Topicwise Separable Sentence Retrieval for Medical Report Generation.

Automated radiology reporting holds immense clinical potential in alleviating the burdensome workload of radiologists and mitigating diagnostic bias. ...

Lung cancer detection with machine learning classifiers with multi-attribute decision-making system and deep learning model.

Diseases of the airways and the other parts of the lung cause chronic respiratory diseases. The major cause of lung disease is tobacco smoke, along wi...

The dawn of the revolution that will allow us to precisely describe how microbiomes function.

The community of microorganisms inhabiting a specific environment, such as the human gut - including bacteria, fungi, archaea, viruses, protozoa, and ...

Unraveling the power of NAP-CNB's machine learning-enhanced tumor neoantigen prediction.

In this study, we present a proof-of-concept classical vaccination experiment that validates the in silico identification of tumor neoantigens (TNAs) ...

Learning Consistent Semantic Representation for Chest X-ray via Anatomical Localization in Self-Supervised Pre-Training.

Despite the similar global structures in Chest X-ray (CXR) images, the same anatomy exhibits varying appearances across images, including differences ...

Artificial intelligence-based deep learning algorithms for ground-glass opacity nodule detection: A review.

Ground-glass opacities (GGOs) are hazy opacities on chest computed tomography (CT) scans that can indicate various lung diseases, including early COVI...

Automated classification of chest X-rays: a deep learning approach with attention mechanisms.

BACKGROUND: Pulmonary diseases such as COVID-19 and pneumonia, are life-threatening conditions, that require prompt and accurate diagnosis for effecti...