Intelligent Alzheimer’s Care: Predictive and Supportive Systems with GNNs and GANs

Alzheimer is a very hard type of disorder due to the progressive impact on memory functions together with other cognitive and daily performances. Traditional approaches were failing at predicting advance and providing individual treatment. In this, have developed an AI technology project based on GNNs for disease prediction and care management process, for which could not find a precedent; coupled with that, use Generative Adversarial Network for stimulating memory and creating patient-friendly environment. Through training of a single drop of brain imaging, cognitive, and environment data, the created system estimates regions which have been thought to contribute to regional development toward Alzheimer’s disease with an accuracy of 97%. It oversees control of recurrent appointments, increases memory throughput via a user-specific media message and aids in post-discharge appointments, which is useful to patients and caretakers in the goal of bettering their experience and quality of life.

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Publication Details

Published
2025-04-17
DOI
https://doi.org/10.1109/incacct65424.2025.11011355
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Intelligent Alzheimer’s Care: Predictive and Supportive Systems with GNNs and GANs

K Sathyabama, V Yuvaraj, Aslam Khan A
Artificial Intelligence in Healthcare
article

Intelligent Alzheimer’s Care: Predictive and Supportive Systems with GNNs and GANs

K Sathyabama, V Yuvaraj, Aslam Khan A
article en

Abstract

Alzheimer is a very hard type of disorder due to the progressive impact on memory functions together with other cognitive and daily performances. Traditional approaches were failing at predicting advance and providing individual treatment. In this, have developed an AI technology project based on GNNs for disease prediction and care management process, for which could not find a precedent; coupled with that, use Generative Adversarial Network for stimulating memory and creating patient-friendly environment. Through training of a single drop of brain imaging, cognitive, and environment data, the created system estimates regions which have been thought to contribute to regional development toward Alzheimer’s disease with an accuracy of 97%. It oversees control of recurrent appointments, increases memory throughput via a user-specific media message and aids in post-discharge appointments, which is useful to patients and caretakers in the goal of bettering their experience and quality of life.

Openalex Percentile: Top 86%
Artificial Intelligence in Healthcare
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