Identifying, screening and monitoring individuals at risk of Alzheimer's disease (AD) and dementia is a formidable challenge. Neuroimaging, and in particular magnetic resonance imaging (MRI), is crucial to detect structural neurodegeneration. However, current quantification tools are mainly limited to research contexts and produce non-standardised results. DIADEMA will build a systematic and standardised workflow to support neuro(radio)logical diagnosis. By combining artificial intelligence (AI) and machine learning (ML) the investigators will significantly enhance the clinical diagnosis of AD in neuroradiology. The investigator's main hypothesis is that an efficient workflow and associated higher diagnostic accuracy will substantially reduce healthcare costs, support clinical decision-making, provide second-opinion tools and improve patient care. This dual advance will have a profound impact on the healthcare system, marking an important step in the fight against Alzheimer's disease and dementia.
Study Type
OBSERVATIONAL
Enrollment
80,000
To evaluate the possibility to improve the neuroradiologic workflow with AI models
Irccs Synlab Sdn
Naples, Italy
Improvement of the neuroradiological workflow performance
ROC curves
Time frame: 1-36 month
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