AIMC Topic: Disease Outbreaks

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CEL: A Continual Learning Model for Disease Outbreak Prediction by Leveraging Domain Adaptation via Elastic Weight Consolidation.

Interdisciplinary sciences, computational life sciences Feb 28, 2025
Continual learning is the ability of a model to learn over time without forgetting previous knowledge. Therefore, adapting new data in dynamic fields like disease outbreak prediction is paramount. Deep neural networks are prone to error due to catast...
Disease Outbreaks Influenza, Human Measles Humans Neural Networks, Computer Machine Learning
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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...
SARS-CoV-2 Disease Outbreaks Incidence ROC Curve Computational Biology Singapore Machine Learning COVID-19 Forecasting Humans
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Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

Journal of medical Internet research Feb 6, 2025
BACKGROUND: Mumps is a viral respiratory disease characterized by facial swelling and transmitted through respiratory secretions. Despite the availability of an effective vaccine, mumps outbreaks have reemerged globally, including in China, where it ...
Forecasting Humans Incidence Female Mumps Disease Outbreaks Male Deep Learning China
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Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.

Artificial intelligence in medicine Feb 1, 2025
BACKGROUND: Controlling re-emerging outbreaks such as COVID-19 is a critical concern to global health. Disease forecasting solutions are extremely beneficial to public health emergency management. This work aims to design and deploy a framework for r...
Pandemics COVID-19 Forecasting Humans Neural Networks, Computer Canada Influenza, Human Coronavirus Infections SARS-CoV-2 Disease Outbreaks Deep Learning Pneumonia, Viral
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A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features.

BMC public health Feb 1, 2025
BACKGROUND: Accurate and timely monitoring of influenza prevalence is essential for effective healthcare interventions. This study proposes a graph neural network (GNN)-based method to address the issue of cross-regional connectivity in predicting in...
Spatio-Temporal Analysis Influenza, Human Graph Neural Networks Neural Networks, Computer Forecasting Disease Outbreaks Humans
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Machine learning reveals the dynamic importance of accessory sequences for outbreak clustering.

mBio Jan 28, 2025
UNLABELLED: Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the vari...
Disease Outbreaks Salmonella Infections Cluster Analysis Genome, Bacterial Whole Genome Sequencing Interspersed Repetitive Sequences Humans Salmonella enterica Machine Learning Molecular Epidemiology Animals
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Machine learning models provide modest accuracy in predicting clinical impact of porcine reproductive and respiratory syndrome type 2 in Canadian sow herds.

American journal of veterinary research Jan 9, 2025
OBJECTIVE: To determine the predictive potential of the open reading frame 5 nucleotide sequence of porcine reproductive and respiratory syndrome (PRRS) virus and the basic demographic data on the severity of the impact on selected production paramet...
Machine Learning Retrospective Studies Female Animals Porcine respiratory and reproductive syndrome virus Disease Outbreaks Swine Ontario Longitudinal Studies Porcine Reproductive and Respiratory Syndrome
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Multi-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model.

PLoS computational biology Jan 9, 2025
Human mobility between different regions is a major factor in large-scale outbreaks of infectious diseases. Deep learning models incorporating infectious disease transmission dynamics for predicting the spread of multi-regional outbreaks due to human...
Epidemiological Models Communicable Diseases Disease Outbreaks Spatio-Temporal Analysis Deep Learning Computational Biology Epidemics Humans Neural Networks, Computer
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Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks.

Scientific reports Dec 31, 2024
Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to effictively mitigate their impact. This study applies advanced machine learning techniques to forec...
Disease Outbreaks Algorithms Humans Dengue Zika Virus Infection Forecasting Machine Learning Chikungunya Fever Communicable Diseases
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Potato Late Blight Outbreak: A Study on Advanced Classification Models Based on Meteorological Data.

Sensors (Basel, Switzerland) Dec 9, 2024
While past research has emphasized the importance of late blight infection detection and classification, anticipating the potato late blight infection is crucial from the economic point of view as it helps to significantly reduce the production cost....
Phytophthora infestans Plant Diseases Solanum tuberosum Humans Disease Outbreaks Machine Learning Logistic Models
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