Unsupervised Machine Learning Using Cerebrospinal Fluid Proteomics for Understanding Parkinson’s Disease Progression

Lubna Abu Zohair*, Hind Zantout, Marta Vallejo, Md Azher Uddin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study explores the potential of advanced, context-aware machine learning algorithms, such as autoencoders, to represent longitudinal cerebrospinal fluid proteomic data, enabling the objective discovery of two patient strata with significance.
Original languageEnglish
Title of host publicationProceedings of the 2025 AAAI Summer Symposium Series
EditorsChristopher W. Geib, Ron Petrick, Abrar Ullah
Place of PublicationDubai, UAE
PublisherAAAI Press
Pages72-74
Number of pages3
Volume6
Edition1
ISBN (Print)1577358996, 9781577358992
DOIs
Publication statusPublished - 1 Aug 2025
EventAAAI 2025 Summer Symposium: Context-Awareness in Cyber-Physical Systems - Heriot-Watt University Dubai, Dubai, United Arab Emirates
Duration: 20 May 202522 May 2025
https://sites.google.com/view/cyber-physical-systems
https://haic2025.com/

Publication series

NameAAAI Summer Symposium Series (SuSS)
PublisherAAAI
Number1
Volume6
ISSN (Print)2994-4317

Conference

ConferenceAAAI 2025 Summer Symposium
Country/TerritoryUnited Arab Emirates
CityDubai
Period20/05/2522/05/25
Internet address

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