{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/personalized-gaussian-processes-for-future","title":"Personalized Gaussian Processes for Future Prediction of Alzheimer's Disease Progression","arxiv_id":"1712.00181","date":"2017-12-01","proceeding":null,"authors":["Kelly Peterson","Ognjen Rudovic","Ricardo Guerrero","Rosalind W. Picard"],"abstract":"In this paper, we introduce the use of a personalized Gaussian Process model\n(pGP) to predict the key metrics of Alzheimer's Disease progression (MMSE,\nADAS-Cog13, CDRSB and CS) based on each patient's previous visits. We start by\nlearning a population-level model using multi-modal data from previously seen\npatients using the base Gaussian Process (GP) regression. Then, this model is\nadapted sequentially over time to a new patient using domain adaptive GPs to\nform the patient's pGP. We show that this new approach, together with an\nauto-regressive formulation, leads to significant improvements in forecasting\nfuture clinical status and cognitive scores for target patients when compared\nto modeling the population with traditional GPs.","url_abs":"http://arxiv.org/abs/1712.00181v4","url_pdf":"http://arxiv.org/pdf/1712.00181v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"personalized-gaussian-processes-for-future","repo_url":"https://github.com/yuriautsumi/PersonalizedGP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"future-prediction","task_name":"Future prediction"},{"task_slug":"gaussian-processes","task_name":"Gaussian Processes"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"gaussian-process","method_name":"Gaussian Process"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}