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Updated: Jun 27, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
An algorithm for the early diagnosis and correct approach to dementia management: results of a multiprofessional team
Pietro Gareri1, Antonino Maria Cotroneo2, Giovanni Gelmini3
1Department of Frailty, Head Physician CDCD Catanzaro Lido - ASP Catanzaro, Viale Crotone 214, 88100, Catanzaro, Italy. pietro.gareri@gmail.com.
Backgroung:
The early identification of cognitive disorder is a primary scope, because it could reduce the rate of severe cognitive impairment and thus contribute to reduce healthcare costs in the next future.
Aims:
The present paper aimed to build a virtuous diagnostic path of cognitive impairment, highlighting all the professionalism that can serve this purpose.
Methods:
The Delphi method was used by the experts, who reviewed the information available during each meeting related to the following topics: early diagnosis of cognitive impairment, definition of Mild Cognitive Impairment, unmet needs in post-stroke patients, critical decision-making nodes in complex patients, risk factors, neuropsychological, imaging diagnosis, blood tests, the criteria for differential diagnosis and the possible treatments.
Results:
The discussion panels analyzed and discussed the available evidences on these topics and the related items. At each meeting, the activities aimed at the creation of a diagnostic-welfare flow chart derived from the proposal of the board and the suggestions of the respondents. Subsequently, the conclusions of each panel were written, and the study group reviewed them until a global consensus was reached. Once this process was completed, the preparation of the final document was carried out.
Conclusions:
Eventually, we built an algorithm for the early diagnosis and treatment, the risk factors, with the possible differences among the different kinds of dementia.
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