DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images
Impact in
- Neurology 172
Classified as
- Journal
- IEEE Access
In The Last Decade
doi.org/10.1109/access.2021.3090474 →Countries where authors are citing DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images
This map shows the geographic impact of DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images more than expected).
Fields of papers citing DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images
This network shows the impact of DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images.
About DEMNET: A Deep Learning Model for Early Diagnosis of Alzheimer Diseases and Dementia From MR Images
This paper, published in 2021, received 246 indexed citations . Written by Suriya Murugan, Chandran Venkatesan, M. G. Sumithra, Xiao‐Zhi Gao, M. Akila and S. Manoharan covering the research area of Neurology and Artificial Intelligence. It is primarily cited by scholars working on Neurology (172 citations), Artificial Intelligence (94 citations), Health Information Management (59 citations), Computer Vision and Pattern Recognition (54 citations) and Psychiatry and Mental health (48 citations). Published in IEEE Access.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.1109/access.2021.3090474.