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A Novel Machine Learning Algorithm to Predict the Lewy Body Dementias

NCT04448340 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 200

Last updated 2020-09-10

No results posted yet for this study

Summary

Parkinson's disease dementia (PDD) and Dementia with lewy bodies (DLB) are dementia syndromes that overlap in many clinical features, making their diagnosis difficult in clinical practice, particularly in advanced stages. We propose a machine learning algorithm, based only on non-invasively and easily in-the-clinic collectable predictors, to identify these disorders with a high prognostic performance.

Conditions

Interventions

DIAGNOSTIC_TEST

machine learning model

Two classification algorithms, logistic regression and K-Nearest Neighbors (K-NNs), were investigated for their ability to predict successfully whether patients suffered from PDD or DLB.

Sponsors & Collaborators

  • National and Kapodistrian University of Athens

    lead OTHER

Principal Investigators

  • ANASTASIA BOUGEA · National and Kapodistrian University of Athens

Eligibility

Min Age
50 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-09-01
Primary Completion
2020-10-01
Completion
2021-03-01

Countries

  • Greece

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04448340 on ClinicalTrials.gov