深度学习在阿尔茨海默病诊断中应用近5年文献的可视化分析

doi:10.3969/j.issn.1006-9771.2022.11.011

Abstract

Abstract:

Objective To analyze the current situation, research hotpots and trends of researches about the application of deep learning in the diagnosis of Alzheimer's disease (AD) in the past five years.

Methods The researches about the application of deep learning in the diagnosis of AD were retrieved in the core database of Web of Science, from 2017 to 2021, and analyzed with CiteSpace 6.1.R3 in terms of annual number of researches, countries/regions, institutions, authors, keywords and references.

Results A total of 306 researches were returned. The annual number increased year by year. United States, South Korea and United Kingdom were the highly influential countries, Chinese Academy of Sciences was the most frequently published and central institution, and Liu M was the author publishing the most researches. The researches mainly focused on the classification of various stages of AD. The classification of AD using independent and complementary multimodal data, and early prediction of AD might become a frontier trend.

Conclusion Deep learning for the diagnosis of AD is mainly used for classification and early prediction of Alzheimer's disease.

Key words: deep learning, Alzheimer's disease, diagnosis, visualized analysis

CLC Number:

R749.1

JIANG Jiarui,NIU Zhendong. Deep learning for diagnosis of Alzheimer's disease in the past five years: a visualized analysis[J]. 《Chinese Journal of Rehabilitation Theory and Practice》, 2022, 28(11): 1318-1324.

Figures/Tables 10

References 46

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频次	关键词	中心性	关键词
168	alzheimers disease	0.48	selection
137	deep learning	0.22	resting state fMRI
104	MCI	0.20	transfer learning
99	classification	0.19	disease
89	diagnosis	0.18	feature ranking
77	MRI	0.16	structural MRI
69	convolutional neural network	0.16	alpha synuclein
48	dementia	0.15	recognition
45	machine learning	0.15	hippocampal
43	prediction	0.15	performance

分类号	大小	轮廓值	关键词
0	41	0.76	segmentation; early diagnosis; pattern; transfer learning; image classification
1	31	0.71	fusion; feature; selection; hippocampal; MRI; feature extraction
2	30	0.92	computer-aided diagnosis; classification; MCI; convolutional neural network; eeg
3	25	0.87	dementia; fMRI; network; recongnition; robust
4	22	0.96	ADNI; PET; sMRI; OASIS; big data
5	22	0.86	support vector machine; progression; deep neural network; machine learning
6	18	0.94	disease; feature ranking; image analysis; ensemble; bioelectronic medicine
7	14	0.93	amyloid beta; alpha synuclein; FDG PET; impairment; neurodegenerative disorder
8	14	0.94	voxel based morphometry; prediction; volumetry; anatomical landmark; patch
9	13	0.88	guideline; feature representation; Mini Mental State; 3d convolutional network; tau

频次	作者	期刊/会议	文题
43	Liu等	IEEE T Bio-Med Eng	Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer's disease
42	Litjens等	Med Image Anal	A survey on deep learning in medical image analysis
36	Basaia等	Neuroimage-Clin	Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks
35	Hosseiniasl等	IEEE Image Proc	Alzheimer's disease diagnostics by adaptation of 3D convolutional network
35	Lecun等	Nature	Deep learning

Deep learning for diagnosis of Alzheimer's disease in the past five years: a visualized analysis

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