AIMC Topic: COVID-19
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A hybrid deep learning model for sentiment analysis of COVID-19 tweets with class balancing.
Scientific reports
Jul 30, 2025
The widespread dissemination of misinformation and the diverse public sentiment observed during the COVID-19 pandemic highlight the necessity for accurate sentiment analysis of social media discourse. This study proposes a hybrid deep learning (DL) m...
COVID-19 risk stratification among older adults: a machine learning approach to identify personal and health-related risk factors.
BMC public health
Jul 29, 2025
BACKGROUND: The COVID-19 pandemic highlighted the need to understand factors influencing individuals' risk perceptions and health behaviors. This study aimed to explore the roles of individuals' knowledge, perception, and health-related issues in det...
Differentiation of COVID-19 from other types of viral pneumonia and severity scoring on baseline chest radiographs: Comparison of deep learning with multi-reader evaluation.
PloS one
Jul 29, 2025
Chest X-ray (CXR) imaging plays a pivotal role in the diagnosis and prognosis of viral pneumonia. However, distinguishing COVID-19 CXRs from other viral infections remains challenging due to highly similar radiographic features. Most existing deep le...
Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter During the COVID-19 Pandemic: A Natural Language Processing Approach.
JMIR infodemiology
Jul 28, 2025
BACKGROUND: User demographics are often hidden in social media data due to privacy concerns. However, demographic information on substance use (SU) can provide valuable insights, allowing public health policy makers to focus on specific cohorts and d...
Multilevel Hydrangea-like Heterogeneous Oxides Enabling COVID-19 Progression Surveillance via Metabolic Fingerprints.
Analytical chemistry
Jul 23, 2025
Coronavirus disease 2019 (COVID-19), a global pandemic infectious disease, requires early diagnosis and dynamic monitoring to enable timely intervention and reduce the risks of adverse outcomes. To support these needs, we developed an advanced metabo...
ViT-GCN: a novel hybrid model for accurate pneumonia diagnosis from x-ray images.
Biomedical physics & engineering express
Jul 21, 2025
This study aims to enhance the accuracy of pneumonia diagnosis from x-ray images by developing a model that integrates Vision Transformer (ViT) and Graph Convolutional Networks (GCN) for improved feature extraction and diagnostic performance. The ViT...
An illustration of multi-class roc analysis for predicting internet addiction among university students.
PloS one
Jul 21, 2025
The internet is one of the essential tools today, and its impact is particularly felt among university students. Internet addiction (IA) has become a serious public health issue worldwide. This multi-class classification study aimed to identify the p...
Detecting Conversation Topics in Recruitment Calls of African American Participants to the All of Us Research Program Using Machine Learning: Model Development and Validation Study.
JMIR formative research
Jul 17, 2025
BACKGROUND: Advancements in science and technology can exacerbate health disparities, particularly when there is a lack of diversity in clinical research, which limits the benefits of innovations for underrepresented communities. Programs like the Al...
Which explanations do clinicians prefer? A comparative evaluation of XAI understandability and actionability in predicting the need for hospitalization.
BMC medical informatics and decision making
Jul 16, 2025
BACKGROUND: This study aims to address the gap in understanding clinicians' attitudes toward explainable AI (XAI) methods applied to machine learning models using tabular data, commonly found in clinical settings. It specifically explores clinicians'...
A novel machine learning architecture to improve classification of intermediate cases in health: workflow and case study for public health.
BMC bioinformatics
Jul 16, 2025
BACKGROUND: The practice of medicine has evolved significantly during the past decade, with the emergence of Machine Learning (ML) that offers the opportunity of personalized patient-tailored care. However, ML models still face some challenges when c...
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