Miguel Ángel Muñoz-Ruiz

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BACKGROUND MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods. OBJECTIVE To compare FTD with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) with three automatic MRI analysis methods - Hippocampal(More)
BACKGROUND The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease. OBJECTIVES We evaluated how well the DSI generalizes across four different cohorts: DESCRIPA, ADNI, AddNeuroMed, and the(More)
BACKGROUND The Disease State Index (DSI) is a method which interprets data originating from multiple different sources, assisting the clinician in the diagnosis and follow-up of dementia diseases. OBJECTIVE We compared the differences in accuracy in differentiating stable mild cognitive impairment (S-MCI) and progressive MCI (P-MCI) obtained from(More)
BACKGROUND Disease State Index (DSI) and its visualization, Disease State Fingerprint (DSF), form a computer-assisted clinical decision making tool that combines patient data and compares them with cases with known outcomes. AIMS To investigate the ability of the DSI to diagnose frontotemporal dementia (FTD) and Alzheimer's disease (AD). METHODS The(More)
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