AIMC Topic: COVID-19

Clear Filters Showing 171 to 180 of 2349 articles

Reliability-enhanced data cleaning in biomedical machine learning using inductive conformal prediction.

PLoS computational biology Feb 13, 2025
Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. Existing approac...
Electronic Health Records COVID-19 Algorithms Humans Female SARS-CoV-2 Machine Learning Reproducibility of Results Breast Neoplasms Computational Biology
View on PubMed DOI

Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.

PLoS computational biology Feb 13, 2025
Forecasting the occurrence and absence of novel disease outbreaks is essential for disease management, yet existing methods are often context-specific, require a long preparation time, and non-outbreak prediction remains understudied. To address this...
Computational Biology Humans Singapore Machine Learning COVID-19 Disease Outbreaks Forecasting SARS-CoV-2 Incidence ROC Curve
View on PubMed DOI

EAMAPG: Explainable Adversarial Model Analysis via Projected Gradient Descent.

Computers in biology and medicine Feb 12, 2025
Despite the outstanding performance of deep learning (DL) models, their interpretability remains a challenging topic. In this study, we address the transparency of DL models in medical image analysis by introducing a novel interpretability method usi...
Brain Neoplasms Eye Diseases COVID-19 Deep Learning Humans Databases, Factual Image Processing, Computer-Assisted SARS-CoV-2 Neural Networks, Computer
View on PubMed DOI

Classifying and fact-checking health-related information about COVID-19 on Twitter/X using machine learning and deep learning models.

BMC medical informatics and decision making Feb 11, 2025
BACKGROUND: Despite recent progress in misinformation detection methods, further investigation is required to develop more robust fact-checking models with particular consideration for the unique challenges of health information sharing. This study a...
Humans Machine Learning COVID-19 Deep Learning Social Media Information Dissemination
View on PubMed DOI

Understanding Citizens' Response to Social Activities on Twitter in US Metropolises During the COVID-19 Recovery Phase Using a Fine-Tuned Large Language Model: Application of AI.

Journal of medical Internet research Feb 11, 2025
BACKGROUND: The COVID-19 pandemic continues to hold an important place in the collective memory as of 2024. As of March 2024, >676 million cases, 6 million deaths, and 13 billion vaccine doses have been reported. It is crucial to evaluate sociopsycho...
Large Language Models COVID-19 Language SARS-CoV-2 Cities United States Social Media Humans Artificial Intelligence Pandemics
View on PubMed DOI

Machine Learning Methods Based on Chest CT for Predicting the Risk of COVID-19-Associated Pulmonary Aspergillosis.

Academic radiology Feb 10, 2025
RATIONALE AND OBJECTIVES: To develop and validate a machine learning model based on chest CT and clinical risk factors to predict secondary aspergillus infection in hospitalized COVID-19 patients.
SARS-CoV-2 Risk Factors Aged Retrospective Studies Humans Risk Assessment Adult Tomography, X-Ray Computed Machine Learning Male Female Predictive Value of Tests Middle Aged COVID-19 Pulmonary Aspergillosis
View on PubMed DOI

Bias Amplification to Facilitate the Systematic Evaluation of Bias Mitigation Methods.

IEEE journal of biomedical and health informatics Feb 10, 2025
The future of artificial intelligence (AI) safety is expected to include bias mitigation methods from development to application. The complexity and integration of these methods could grow in conjunction with advances in AI and human-AI interactions....
SARS-CoV-2 Male Bias Radiography, Thoracic Artificial Intelligence COVID-19 Female Humans
View on PubMed DOI

UnBias: Unveiling Bias Implications in Deep Learning Models for Healthcare Applications.

IEEE journal of biomedical and health informatics Feb 10, 2025
The rapid integration of deep learning-powered artificial intelligence systems in diverse applications such as healthcare, credit assessment, employment, and criminal justice has raised concerns about their fairness, particularly in how they handle v...
SARS-CoV-2 Male Deep Learning COVID-19 Female Bias Humans Neural Networks, Computer
View on PubMed DOI

Forecasting Epidemic Spread With Recurrent Graph Gate Fusion Transformers.

IEEE journal of biomedical and health informatics Feb 10, 2025
Predicting the unprecedented, nonlinear nature of COVID-19 presents a significant public health challenge. Recent advances in deep learning, such as graph neural networks (GNNs), recurrent neural networks (RNNs), and Transformers, have enhanced predi...
COVID-19 Forecasting SARS-CoV-2 Humans Neural Networks, Computer Deep Learning
View on PubMed DOI

Joint Energy-Based Model for Semi-Supervised Respiratory Sound Classification: A Method of Insensitive to Distribution Mismatch.

IEEE journal of biomedical and health informatics Feb 10, 2025
Semi-supervised learning effectively mitigates the lack of labeled data by introducing extensive unlabeled data. Despite achieving success in respiratory sound classification, in practice, it usually takes years to acquire a sufficiently sizeable unl...
Signal Processing, Computer-Assisted Supervised Machine Learning Respiratory Sounds COVID-19 Humans Algorithms SARS-CoV-2
View on PubMed DOI
Popular Topics
Recent Journals