干旱区生态环境知识资源中心(Arid): Deep learning based computer aided diagnosis of Alzheimer's disease: a snapshot of last 5 years, gaps, and future directions

Arid

DOI	10.1007/s10462-023-10644-8
	Deep learning based computer aided diagnosis of Alzheimer's disease: a snapshot of last 5 years, gaps, and future directions
	Bhandarkar, Anish; Naik, Pratham; Vakkund, Kavita; Junjappanavar, Srasthi; Bakare, Savita; Pattar, Santosh
通讯作者	Bhandarkar, A
来源期刊	ARTIFICIAL INTELLIGENCE REVIEW
ISSN	0269-2821
EISSN	1573-7462
出版年	2024
卷号	57 期号:2
英文摘要	Alzheimer's disease affects around one in every nine persons among the elderly population. Being a neurodegenerative disease, its cure has not been established till date and is managed through supportive care by the health care providers. Thus, early diagnosis of this disease is a crucial step towards its treatment plan. There exist several diagnostic procedures viz., clinical, scans, biomedical, psychological, and others for the disease's detection. Computer-aided diagnostic techniques aid in the early detection of this disease and in the past, several such mechanisms have been proposed. These techniques utilize machine learning models to develop a disease classification system. However, the focus of these systems has now gradually shifted to the newer deep learning models. In this regards, this article aims in providing a comprehensive review of the present state-of-the-art techniques as a snapshot of the last 5 years. It also summarizes various tools and datasets available for the development of the early diagnostic systems that provide fundamentals of this field to a novice researcher. Finally, we discussed the need for exploring biomarkers, identification and extraction of relevant features, trade-off between traditional machine learning and deep learning models and the essence of multimodal datasets. This enables both medical, engineering researchers and developers to address the identified gaps and develop an effective diagnostic system for the Alzheimer's disease.
英文关键词	Alzheimer's disease Computer aided diagnosis Deep learning Multimodal test diagnosis Traditional versus DL models
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:001161053700001
WOS关键词	CLINICAL-PRACTICE ; FEATURE-SELECTION ; NEURAL-NETWORK ; DEMENTIA ; RISK ; MRI ; CLASSIFICATION ; PROGRESSION ; PREDICTION ; OASIS
WOS类目	Computer Science, Artificial Intelligence
WOS研究方向	Computer Science
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/402959
推荐引用方式 GB/T 7714	Bhandarkar, Anish,Naik, Pratham,Vakkund, Kavita,et al. Deep learning based computer aided diagnosis of Alzheimer's disease: a snapshot of last 5 years, gaps, and future directions[J],2024,57(2).
APA	Bhandarkar, Anish,Naik, Pratham,Vakkund, Kavita,Junjappanavar, Srasthi,Bakare, Savita,&Pattar, Santosh.(2024).Deep learning based computer aided diagnosis of Alzheimer's disease: a snapshot of last 5 years, gaps, and future directions.ARTIFICIAL INTELLIGENCE REVIEW,57(2).
MLA	Bhandarkar, Anish,et al."Deep learning based computer aided diagnosis of Alzheimer's disease: a snapshot of last 5 years, gaps, and future directions".ARTIFICIAL INTELLIGENCE REVIEW 57.2(2024).