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Updated: Feb 21, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Scheduling and Modeling a Cognitive Assessment Guide for Screening AD by Primary Care Physicians
Maria Sagiadinou1, Antigoni Avramouli2, Panayiotis M Vlamos2
1Department of Informatics, Ionian University, Corfu, 49100, Greece. c15sagi@ionio.gr.
This study proposes a practical guideline for primary care physicians to improve early Alzheimer's Disease (AD) detection. A two-visit approach with specific screening questions and automated scoring aims to aid diagnosis and patient care.
Area of Science:
- Neurology
- Geriatrics
- Primary Care Medicine
Background:
- Alzheimer's Disease (AD) is a clinicobiological entity with long preclinical and presymptomatic phases.
- Early detection and diagnosis are crucial for effective patient management and caregiver support.
- Primary care physicians are often the first to identify cognitive impairment but may hesitate in screening.
Purpose of the Study:
- To model a practical guideline for mental assessment and screening for primary care physicians.
- To integrate screening into a step-by-step medical instruction policy.
- To facilitate earlier diagnosis of Alzheimer's Disease in primary care settings.
Main Methods:
- A comprehensive literature review was conducted.
- A two-visit approach for patient assessment was designed.
- The approach includes specific close-ended questions and automated scoring of screening tests.
Main Results:
- A structured, two-visit guideline for Alzheimer's screening was developed.
- The proposed method includes easily accessible tests with immediate score calculation.
- The guideline aims to overcome primary care physician reluctance towards screening.
Conclusions:
- The proposed guideline offers a practical framework for early Alzheimer's Disease detection in primary care.
- This approach can empower primary care physicians in the diagnostic process.
- Further clinical trials are planned to validate the guideline's effectiveness.
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