AIMC Topic: Communicable Diseases

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Machine learning approaches for real-time ZIP code and county-level estimation of state-wide infectious disease hospitalizations using local health system data.

Epidemics
The lack of conventional methods of estimating real-time infectious disease burden in granular regions inhibits timely and efficient public health response. Comprehensive data sources (e.g., state health department data) typically needed for such est...

Protocol for human evaluation of generative artificial intelligence chatbots in clinical consultations.

PloS one
BACKGROUND: Generative artificial intelligence (GenAI) has the potential to revolutionise healthcare delivery. The nuances of real-life clinical practice and complex clinical environments demand a rigorous, evidence-based approach to ensure safe and ...

An extensive review on infectious disease diagnosis using machine learning techniques and next generation sequencing: State-of-the-art and perspectives.

Computers in biology and medicine
UNLABELLED: Infectious diseases, including tuberculosis (TB), HIV/AIDS, and emerging pathogens like COVID-19 pose severe global health challenges due to their rapid spread and significant morbidity and mortality rates. Next-generation sequencing (NGS...

Artificial intelligence for modelling infectious disease epidemics.

Nature
Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social sci...

Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges.

Nature communications
Integrating prior epidemiological knowledge embedded within mechanistic models with the data-mining capabilities of artificial intelligence (AI) offers transformative potential for epidemiological modeling. While the fusion of AI and traditional mech...

Multi-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model.

PLoS computational biology
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...

Leveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks.

Scientific reports
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...

A study of novel linear Diophantine fuzzy topological numbers and their application to communicable diseases.

The European physical journal. E, Soft matter
The idea of linear Diophantine fuzzy sets (LDFs) is a novel tool for analysis, soft computing, and optimization. Recently, the concept of a linear Diophantine fuzzy graph has been proposed in 2022. The aim of this research is to extend topological nu...

Dynamics of infectious disease mathematical model through unsupervised stochastic neural network paradigm.

Computational biology and chemistry
The viruses has spread globally and have been impacted lives of people socially and economically, which causes immense suffering throughout the world. Thousands of people died and millions of illnesses were brought, by the outbreak worldwide. In orde...

Artificial intelligence-powered image analysis: A paradigm shift in infectious disease detection.

Artificial intelligence in medicine
The global burden of infectious diseases significantly affects mortality rates, with their varying symptoms making it challenging to assess and determine the severity of infections. Different countries face unique challenges related to these diseases...