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Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis
Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis
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Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis
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Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis
Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis

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Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis
Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis
Journal Article

Using Artificial Neural Network Models (ANNs) to Identify Patients with Idiopathic Normal Pressure Hydrocephalus (INPH) and Alzheimer Dementia (AD): Clinical Psychological Features and Differential Diagnosis

2025
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Overview
Background and Objectives: Patients with idiopathic normal pressure hydrocephalus (INPH) present similar symptoms as other diseases, such as dementia (AD). However, while dementia is not reversible, INPH dementia can be treated through neurosurgery. This study aims to assess the Rorschach method as a valid tool to identify INPH patients. Materials and Methods: The perception characteristics of a small sample of patients (n = 19) were observed through the Rorschach Inblok test. Artificial neural network (ANN) models allowed us to analyze the correlations between patients’ cognitive functions and perception characteristics. Results: The results obtained revealed significant insights about the independent traits in patients’ patterns of response with INPH and AD. In performing the test, patients with INPH and AD concentrated more on the cards displayed and what they perceived, while other patients concentrated on reactions related to the image proposed. Conclusions: The Rorschach test is a valid predictor tool to identify INPH patients who could successfully be treated with neurosurgery. Hence, this methodology has potential in differential diagnosis applied to a clinical context.