For: | Byeon H. Screening dementia and predicting high dementia risk groups using machine learning. World J Psychiatry 2022; 12(2): 204-211 [PMID: 35317343 DOI: 10.5498/wjp.v12.i2.204] |
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URL: | https://www.wjgnet.com/2220-3206/full/v12/i2/204.htm |
Number | Citing Articles |
1 |
Kadir Uludag. Clinical Practice and Unmet Challenges in AI-Enhanced Healthcare Systems. Advances in Medical Technologies and Clinical Practice 2024; : 207 doi: 10.4018/979-8-3693-2703-6.ch011
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2 |
Samuel O. Danso, Sindhu Prattipati, Ibrahim Alqatawneh, Georgios Ntailianis. Exploration of Machine Learning and Deep Learning Architectures for Dementia Risk Prediction Based on ATN Framework. 2024 29th International Conference on Automation and Computing (ICAC) 2024; : 1 doi: 10.1109/ICAC61394.2024.10718816
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3 |
Paul E. Rapp, Christopher Cellucci, David Darmon, David Keyser. Cautionary Observations Concerning the Introduction of Psychophysiological Biomarkers into Neuropsychiatric Practice. Psychiatry International 2022; 3(2): 181 doi: 10.3390/psychiatryint3020015
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4 |
Silvia Ottaviani, Fiammetta Monacelli. Rethinking Dementia Risk Prediction: A Critical Evaluation of a Multimodal Machine Learning Predictive Model. Journal of Alzheimer's Disease 2024; 97(3): 1097 doi: 10.3233/JAD-231071
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5 |
Haewon Byeon. Innovative approaches to managing chronic multimorbidity: A multidisciplinary perspective. World Journal of Clinical Cases 2025; 13(19): 102484 doi: 10.12998/wjcc.v13.i19.102484
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6 |
Swati Gupta, Jolly Parikh, Rachna Jain, Namit Kashi, Piyush Khurana, Janya Mehta, Jude Hemanth. Dementia detection using parameter optimization for multimodal datasets. Intelligent Decision Technologies 2024; 18(1): 343 doi: 10.3233/IDT-230532
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