AI Medical Compendium Journal:
Annali di igiene : medicina preventiva e di comunita

Showing 1 to 5 of 5 articles

Machine learning vs. regression models to predict the risk of Legionella contamination in a hospital water network.

Annali di igiene : medicina preventiva e di comunita
INTRODUCTION: The periodic monitoring of Legionella in hospital water networks allows preventive measures to be taken to avoid the risk of legionellosis to patients and healthcare workers.

Natural language processing and String Metric-assisted Assessment of Semantic Heterogeneity method for capturing and standardizing unstructured nursing activities in a hospital setting: a retrospective study.

Annali di igiene : medicina preventiva e di comunita
BACKGROUND: Nurses record data in electronic health records (EHRs) using different terminologies and coding systems. The purpose of this study was to identify unstructured free-text nursing activities recorded by nurses in EHRs with natural language ...

Application of machine learning techniques to physical and rehabilitative medicine.

Annali di igiene : medicina preventiva e di comunita
Nowadays, digital information has increased exponentially in every field to such an extent that it generates huge amounts of electronic data, namely Big Data. In the field of Artificial Intelligence, Machine Learning can be exploited in order to tran...

Vaccination hesitancy: agreement between WHO and ChatGPT-4.0 or Gemini Advanced.

Annali di igiene : medicina preventiva e di comunita
BACKGROUND: An increasing number of individuals use online Artificial Intelligence (AI) - based chatbots to retrieve information on health-related topics. This study aims to evaluate the accuracy in answering vaccine-related answers of the currently ...

Hierarchical convolutional models for automatic pneu-monia diagnosis based on X-ray images: new strategies in public health.

Annali di igiene : medicina preventiva e di comunita
CONCLUSIONS: Despite some limits, our findings support the notion that deep learning methods can be used to simplify the diagnostic process and improve disease management.