Machine Learning

Wen, C., Tu, W., Sebastiani, G. et al. Sex differences in mortality risk profiles across the life course in metabolic dysfunction-associated steatotic liver disease: a machine learning analysis of the Canadian Longitudinal Study on Aging. Biol Sex Differ (2026). https://doi.org/10.1186/s13293-026-00992-9

Samico GA, da Costa DR, Scherer R, Azizi A, Rabinowitz AS, Malek DA, Gracitelli CPB, Medeiros FA. Deep Learning-Predicted RNFL Loss and Incident Glaucoma in the Canadian Longitudinal Study on Aging. Ophthalmol Glaucoma. 2026 Mar 18:S2589-4196(26)00051-7. doi: 10.1016/j.ogla.2026.03.006. Epub ahead of print. PMID: 41862096.

Alaka SA, Ngan SC, MacPherson RE, Pickett W, Chen CP, Sze SK. Enhancing dementia risk prediction with heart rate and machine learning in the Canadian Longitudinal Study on Aging. J Alzheimers Dis. 2025 Oct 29:13872877251390562. doi: 10.1177/13872877251390562. Epub ahead of print. PMID: 41160465.

Li Y, Song Y, Sui J, Greiner R, Li XM, Greenshaw AJ, Liu YS, Cao B. Prospective prediction of anxiety onset in the Canadian longitudinal study on aging (CLSA): A machine learning study. J Affect Disord. 2024 Jul 15;357:148-155. doi: 10.1016/j.jad.2024.04.098. Epub 2024 Apr 24. PMID: 38670463.

Singh S, Zhong S, Rogers K, Hachinski V, Frisbee S. Prioritizing determinants of cognitive function in healthy middle-aged and older adults: insights from a machine learning regression approach in the Canadian longitudinal study on aging. Front Public Health. 2023 Dec 22;11:1290064. doi: 10.3389/fpubh.2023.1290064. Erratum in: Front Public Health. 2024 Feb 12;12:1372914. PMID: 38186704; PMCID: PMC10768541.

Ammar A, Alsadi N, Adachi JD, Gadsden SA, SE Quenneville. A CNN-based strategy to automate contour detection of the hip and proximal femur using DXA hip images from longitudinal databases (CLSA and CaMos). Comput Methods Biomech Biomed Eng Imaging Vis. 2023 Dec 23. DOI: 10.1080/21681163.2023.2296626

Song Y, Qian L, Sui J, Greiner R, Li XM, Greenshaw AJ, Liu YS, Cao B. Prediction of depression onset risk among middle-aged and elderly adults using machine learning and Canadian Longitudinal Study on Aging cohort. J Affect Disord. 2023 Jun 26:S0165-0327(23)00797-8. doi: 10.1016/j.jad.2023.06.031. Epub ahead of print. PMID: 37380110.

Monchka BA, Schousboe JT, Davidson MJ, Kimelman D, Hans D, Raina P, Leslie WD. Development of a manufacturer-independent convolutional neural network for the automated identification of vertebral compression fractures in vertebral fracture assessment images using active learning. Bone. 2022 Aug;161:116427. doi: 10.1016/j.bone.2022.116427. Epub 2022 Apr 27. PMID: 35489707.

Corbin D, Lesage F. Assessment of the predictive potential of cognitive scores from retinal images and retinal fundus metadata via deep learning using the CLSA database. Sci Rep. 2022 Apr 6;12(1):5767. doi: 10.1038/s41598-022-09719-3. PMID: 35388080.

Han X, Steven K, Qassim A, Marshall HN, Bean C, Tremeer M, An J, Siggs OM, Gharahkhani P, Craig JE, Hewitt AW, Trzaskowski M, MacGregor S. Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA. Am J Hum Genet. 2021 Jul 1;108(7):1204-1216. doi: 10.1016/j.ajhg.2021.05.005. Epub 2021 Jun 1. PMID: 34077762; PMCID: PMC8322932.

Wister A, Rosenkrantz L, Shashank A, Walker BB, Schuurman N. Multimorbidity and Socioeconomic Deprivation among Older Adults: A Cross-sectional Analysis in Five Canadian Cities Using the CLSA. 2020 Mar 12. J Aging Health. 2020;34(4):435-454. doi: https://doi.org/10.1080/26892618.2020.1734138