Dataset Information

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features.

ABSTRACT:

Purpose

Cognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment.

Methods

In this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with and without cognitive impairment based on T1-weighted structural MRI. The Montreal cognitive assessment score served as an index of the cognitive status of the patients.

Results

The classifier could identify T2DM-related cognitive decline with a classification accuracy of 84.85% and achieved an area under the curve of 92.65%.

Conclusions

The model can help clinicians analyze and predict cognitive impairment in patients and enable early treatment.

SUBMITTER: Tan X

PROVIDER: S-EPMC9344913 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features.

Tan Xin X Wu Jinjian J Ma Xiaomeng X Kang Shangyu S Yue Xiaomei X Rao Yawen Y Li Yifan Y Huang Haoming H Chen Yuna Y Lyu Wenjiao W Qin Chunhong C Li Mingrui M Feng Yue Y Liang Yi Y Qiu Shijun S

Frontiers in neuroscience 20220719

<h4>Purpose</h4>Cognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment.<h4>Methods</h4>In this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with ...[more]

PMID: 35928014

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Dataset Information

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features.

Purpose

Methods

Results

Conclusions

Publications

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features.

Similar Datasets

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