Early Detection of Alzheimer’s Disease From Cortical and Hippocampal Local Field Potentials Using an Ensembled Machine Learning Model
Author:
Affiliation:
1. Department of Computer Science, Nottingham Trent University, Nottingham, U.K
2. Department of Biomedical Sciences, University of Padova, Padova, Italy
3. Department of Physiology and Pharmacology, Sapienza Università di Roma, Rome, Italy
Funder
Nottingham Trent University Vice Chancellor’s Doctoral Fellowship
Nottingham Trent University’s Strategic Research Theme Springboard Fund
Italian Ministry of Education, Universities and Research
Cristina Fasolato
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation
Link
http://xplorestaging.ieee.org/ielx7/7333/10031624/10159362.pdf?arnumber=10159362
Reference44 articles.
1. Applications of Deep Learning and Reinforcement Learning to Biological Data
2. The CA1 Region of the Human Hippocampus Is a Hot Spot in Alzheimer's Disease
3. Application of explainable artificial intelligence in Alzheimer’s disease classification: A systematic review;vimbi;SquareTrade Research,2023
4. Adult hippocampal neurogenesis in aging and Alzheimer’s disease;babcock;Stem Cell Rep,2021
5. Machine learning techniques for the diagnosis of Alzheimer’s disease: A review;tanveer;ACM Trans Multimedia Comput Commun Appl,2020
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1. A Comparative Study of Pretrained Deep Neural Networks for Classifying Alzheimer's and Parkinson's Disease;2023 IEEE Symposium Series on Computational Intelligence (SSCI);2023-12-05
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