TE-SSL : Time and Event-aware Self Supervised Learning for Alzheimer’s Disease Progression Analysis
| dc.contributor.author | Thrasher, Jacob | |
| dc.contributor.author | Devkota, Alina | |
| dc.contributor.author | Tafti, Ahmed P. | |
| dc.contributor.author | Bhattarai, Binod | |
| dc.contributor.author | Gyawali, Prashnna | |
| dc.contributor.institution | University of Aberdeen.Computing Science | en |
| dc.date.accessioned | 2025-03-20T11:57:01Z | |
| dc.date.available | 2025-03-20T11:57:01Z | |
| dc.date.issued | 2024-10-23 | |
| dc.description | Acknowledgments. This research was supported by West Virginia Higher Education Policy Commission’s Research Challenge Grant Program 2023 and DARPA/FIU AI-CRAFT grant. Data collection and sharing for the Alzheimer’s Disease Neuroimaging Initiative (ADNI) is funded by the National Institute on Aging (National Institutes of Health Grant U19 AG024904). The grantee organization is the Northern California Institute for Research and Education. In the past, ADNI has also received funding from the National Institute of Biomedical Imaging and Bioengineering, the Canadian Institutes of Health Research, and private sector contributions through the Foundation for the National Institutes of Health (FNIH) including generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. | en |
| dc.format.extent | 1863841 | |
| dc.identifier | 302369518 | |
| dc.identifier | cc25e564-b425-4536-aef0-43aa722cac96 | |
| dc.identifier | 85208193092 | |
| dc.identifier.citation | Thrasher, J, Devkota, A, Tafti, A P, Bhattarai, B & Gyawali, P 2024, TE-SSL : Time and Event-aware Self Supervised Learning for Alzheimer’s Disease Progression Analysis . in Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 : 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part XII. Lecture Notes in Computer Science, no. 15012, Springer Nature, pp. 324-333, MICCAI 2024, Marrakesh, Morocco, 6/10/24. https://doi.org/10.1007/978-3-031-72390-2_31 | en |
| dc.identifier.citation | conference | en |
| dc.identifier.doi | 10.1007/978-3-031-72390-2_31 | |
| dc.identifier.isbn | 978-3-031-72389-6 | |
| dc.identifier.isbn | 978-3-031-72390-2 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.other | ORCID: /0000-0001-7171-6469/work/180763437 | |
| dc.identifier.uri | https://hdl.handle.net/2164/25166 | |
| dc.identifier.url | https://www.scopus.com/pages/publications/85208193092 | en |
| dc.language.iso | eng | |
| dc.publisher | Springer Nature | |
| dc.relation.ispartof | Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 | en |
| dc.relation.ispartofseries | Lecture Notes in Computer Science | en |
| dc.subject | Alzheimer’s | en |
| dc.subject | Survival Analysis | en |
| dc.subject | Self-supervised learning | en |
| dc.subject | QA75 Electronic computers. Computer science | en |
| dc.subject | R Medicine | en |
| dc.subject.lcc | QA75 | en |
| dc.subject.lcc | R | en |
| dc.title | TE-SSL : Time and Event-aware Self Supervised Learning for Alzheimer’s Disease Progression Analysis | en |
| dc.type | Conference item | en |
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