From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline | Paper Citation Record

Observation a8a896f3-7f38-451b-a43e-ef6211c47a0f · outbound

This paper cites Alzheimer’s disease: epidemiology and clinical progression.Neurology and therapy, 11(2): 553–569, 2022.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Alzheimer’s disease: epidemiology and clinical progression.Neurology and therapy, 11(2): 553–569, 2022

Reference 1

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Observation a5c9d6c3-d554-4fc1-ab92-96387ade2af3 · outbound

This paper cites The challenging concept of preclinical alzheimer’s disease.Revue Neurologique, 181(9):881–892, 2025.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline The challenging concept of preclinical alzheimer’s disease.Revue Neurologique, 181(9):881–892, 2025

Reference 2

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This paper cites Alzheimer’s disease–why we need early diagnosis.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Alzheimer’s disease–why we need early diagnosis

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

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This paper cites The best treatment is prevention: preven- tion of cognitive decline and dementia–current state, gaps and next steps–.Neurological Research and Practice, 8(1):30, 2026.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline The best treatment is prevention: preven- tion of cognitive decline and dementia–current state, gaps and next steps–.Neurological Research and Practice, 8(1):30, 2026

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This paper cites Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions

Reference 6

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This paper cites The cognitive reserve hypothesis: a longitudinal examination of age-associated declines in reasoning and processing speed.Developmental psychology, 45(2):431, 2009.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline The cognitive reserve hypothesis: a longitudinal examination of age-associated declines in reasoning and processing speed.Developmental psychology, 45(2):431, 2009

Reference 7

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This paper cites The challenges of implementing hybrid baselines for the interpretation of longitudinal behavioral data from individuals.npj Digital Medicine, 9 (1):331, 2026.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline The challenges of implementing hybrid baselines for the interpretation of longitudinal behavioral data from individuals.npj Digital Medicine, 9 (1):331, 2026

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.470972Z

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This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-05T10:39:08.460880Z

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Observation 4c4180dd-1180-4cb8-b3d3-038ba502a796 · outbound

This paper cites Lack of group-to-individual generalizability is a threat to human subjects research.Proceedings of the National Academy of Sciences, 115(27):E6106–E6115, 2018.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Lack of group-to-individual generalizability is a threat to human subjects research.Proceedings of the National Academy of Sciences, 115(27):E6106–E6115, 2018

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Observation 1032b45e-3ed3-4e2d-87e1-32453c765e43 · outbound

This paper cites Expanding the use of brief cognitive assessments to detect suspected early-stage cognitive impairment in primary care.Alzheimer’s & Dementia, 19(9):4252–4259, 2023.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Expanding the use of brief cognitive assessments to detect suspected early-stage cognitive impairment in primary care.Alzheimer’s & Dementia, 19(9):4252–4259, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.439797Z

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Observation d23b32d5-5d2a-47ed-b020-28169e7c50f9 · outbound

This paper cites Accessible analysis of longitudinal data with linear mixed effects models.Disease Models & Mechanisms, 15(5): dmm048025, 2022.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Accessible analysis of longitudinal data with linear mixed effects models.Disease Models & Mechanisms, 15(5): dmm048025, 2022

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.429243Z

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This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 13

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This paper cites Evaluating the performance of bayesian and frequentist approaches for longitudinal modeling: application to alzheimer’s disease.Scientific Reports, 12(1):14448, 2022.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Evaluating the performance of bayesian and frequentist approaches for longitudinal modeling: application to alzheimer’s disease.Scientific Reports, 12(1):14448, 2022

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.407776Z

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Observation d61ce51b-c0b1-4ddc-98b3-95e9d0c675e8 · outbound

This paper cites That blup is a good thing: the estimation of random effects.Statistical science, pages 15–32, 1991.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline That blup is a good thing: the estimation of random effects.Statistical science, pages 15–32, 1991

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Observation 6f59c815-3643-4867-97a5-685ae2abce66 · outbound

This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

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Resolution: unresolved; raw_fallback, observed 2026-08-05T10:39:08.387026Z

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Observation 5d5fcba7-6d9d-4531-9355-c58229dfcb93 · outbound

This paper cites Misuse of the linear mixed model when evaluating risk factors of cognitive decline.American journal of epidemiology, 174(9):1077–1088, 2011.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Misuse of the linear mixed model when evaluating risk factors of cognitive decline.American journal of epidemiology, 174(9):1077–1088, 2011

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.376796Z

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Observation 6b68bbf9-43fc-4810-9bad-ec78d917c0b3 · outbound

This paper cites Instantiated mixed effects modeling of alzheimer’s disease markers.NeuroImage, 142:113–125, 2016.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Instantiated mixed effects modeling of alzheimer’s disease markers.NeuroImage, 142:113–125, 2016

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.366392Z

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Observation 7a373be0-d4ca-4246-a308-b4932f3509b1 · outbound

This paper cites An improved model for disease progression in patients from the alzheimer’s disease neuroimaging initiative.The Journal of Clinical Pharmacology, 52(5):629–644, 2012.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline An improved model for disease progression in patients from the alzheimer’s disease neuroimaging initiative.The Journal of Clinical Pharmacology, 52(5):629–644, 2012

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Observation a7b19804-3de1-4b4c-ba7b-c351e541fc96 · outbound

This paper cites Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data.Biometrics, 67(3):819–829, 2011.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Dynamic predictions and prospective accuracy in joint models for longitudinal and time-to-event data.Biometrics, 67(3):819–829, 2011

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Resolution: unresolved; no resolver link, observed 2026-08-05T10:39:01.843280Z

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Observation 4c6d58da-f9c4-40f2-ae93-b2e712aef410 · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline A state-space approach for longitudinal outcomes: An application to neuropsychological outcomes.Statistical Methods in Medical Research, 31 (3):520–533, 2022

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Observation 58dfc65b-b3e3-44a3-b1dc-e3acc4e176bf · outbound

This paper cites Forecasting the prevalence of preclinical and clinical alzheimer’s disease in the united states.Alzheimer’s & Dementia, 14(2):121–129, 2018.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Forecasting the prevalence of preclinical and clinical alzheimer’s disease in the united states.Alzheimer’s & Dementia, 14(2):121–129, 2018

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.328218Z

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Observation f52536e5-b3e1-4164-aa3c-8b409a6f8f80 · outbound

This paper cites Mills, Allan Lawrie, David G.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Mills, Allan Lawrie, David G

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Observation 8c0e3126-2d44-4270-befd-3c6a81b466f8 · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Forecasting individual progression trajectories in alzheimer’s disease

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Observation 8dc5f9c4-3c58-43da-9ae8-43642aefcf34 · outbound

This paper cites Reflections on dynamic prediction of alzheimer’s disease: advancements in modeling longitudinal outcomes and time-to-event data.BMC Medical Research Methodology, 25, 2025.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Reflections on dynamic prediction of alzheimer’s disease: advancements in modeling longitudinal outcomes and time-to-event data.BMC Medical Research Methodology, 25, 2025

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Observation 371af631-18a0-45f6-b657-fa39ef0058f8 · outbound

This paper cites Applying deep learning to predicting dementia and mild cognitive impairment.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Applying deep learning to predicting dementia and mild cognitive impairment

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Observation 30de49ad-e8be-4909-9e75-9d2e08e854b2 · outbound

This paper cites Prediction of progression from mild cognitive impairment to alzheimer’s disease with longitudinal and multimodal data.Frontiers in dementia, 2: 1271680, 2023.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Prediction of progression from mild cognitive impairment to alzheimer’s disease with longitudinal and multimodal data.Frontiers in dementia, 2: 1271680, 2023

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Observation 6461bd2d-e326-4c90-a824-869982750a81 · outbound

This paper cites Modeling alzheimer’s disease progression using deep recurrent neural networks.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Modeling alzheimer’s disease progression using deep recurrent neural networks

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Observation 938f931f-9512-4279-bde4-35d60b652835 · outbound

This paper cites Longitudinal methods for alzheimer’s cognitive status prediction with deep learning.Alzheimer’s & Dementia, 21 (9):e70488, 2025.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Longitudinal methods for alzheimer’s cognitive status prediction with deep learning.Alzheimer’s & Dementia, 21 (9):e70488, 2025

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Observation 8b34a1d2-d7f3-4f75-baa9-5fd9fbc2607f · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Deep learning in alzheimer’s disease: diagnostic classification and prognostic prediction using neuroimaging data.Frontiers in aging neuroscience, 11:220, 2019

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Observation 2a58126b-ff0c-42ab-a905-473303893c6a · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Transparency of machine-learning in healthcare: The gdpr & european health law.Computer Law & Security Review, 43:105611, 2021

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Observation f6893644-eeee-41e8-9f07-0a830136de84 · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Machine learning approaches for speech-based alzheimer’s detection: a comprehensive survey.Computers, 14(2):36, 2025

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Observation be27103b-4241-4194-9349-d857625ae199 · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Evaluation of speech-based digital biomarkers: review and recommenda- tions.Digital biomarkers, 4(3):99–108, 2020

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Observation 07787e4f-1234-44c8-ada3-72e040bc7ab7 · outbound

This paper cites Resting state eeg biomarkers of cognitive decline associated with alzheimer’s disease and mild cognitive impairment.PloS one, 16(2):e0244180, 2021.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Resting state eeg biomarkers of cognitive decline associated with alzheimer’s disease and mild cognitive impairment.PloS one, 16(2):e0244180, 2021

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Observation 3bb9d609-b186-4f4b-92bc-c7b4b24f2d09 · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Neuroimaging advances regarding subjective cognitive decline in preclinical alzheimer’s disease.Molecular Neurodegeneration, 15(1):55, 2020

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Observation 01b9b68a-31f0-4423-aaed-e8a5d3d66918 · outbound

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From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Imaging biomarkers associated with cognitive decline: a review.Biological psychiatry, 77(8):685–692, 2015

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Observation 11b069fd-0664-46aa-af42-060022888a0a · outbound

This paper cites Schein, Alexandrin Popescul, Lyle H.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Schein, Alexandrin Popescul, Lyle H

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Source-reported events for the cited work

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Observation e38a8178-fd32-470d-8185-6ec897b88e34 · outbound

This paper cites A systematic literature review of solutions for cold start problem.International Journal of System Assurance Engineering and Management, 15:2818–2852, 2024.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline A systematic literature review of solutions for cold start problem.International Journal of System Assurance Engineering and Management, 15:2818–2852, 2024

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Observation 91f88141-7e34-43d9-8f79-311761d2ca58 · outbound

This paper cites Sachs, Gordon J.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Sachs, Gordon J

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Observation 848b058f-2cb7-4854-b854-8e2185f2d591 · outbound

This paper cites Ferri, Mariella Guerra, Yueqin Huang, K.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Ferri, Mariella Guerra, Yueqin Huang, K

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Observation af335ff9-4474-472d-b46e-a28c9291d437 · outbound

This paper cites Fjell, Linda McEvoy, Dominic Holland, Anders M.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Fjell, Linda McEvoy, Dominic Holland, Anders M

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Observation f5c8b4cb-8e4f-42b2-bd3f-6b26ef2745ee · outbound

This paper cites Harada, Marissa C.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Harada, Marissa C

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Source-reported events for the cited work

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Observation f7370c71-3e85-463b-871b-f2a3ec1754db · outbound

This paper cites Intelligible models for classification and regression.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Intelligible models for classification and regression

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Source-reported events for the cited work

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Observation cb88da67-a68f-4bd0-82f6-2c57fcc27d83 · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nature machine intelligence, 1(5):206–215, 2019.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Nature machine intelligence, 1(5):206–215, 2019

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Observation 6e5dc743-5bea-415f-85e5-8a73e5130286 · outbound

This paper cites InterpretML: A Unified Framework for Machine Learning Interpretability.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline InterpretML: A Unified Framework for Machine Learning Interpretability

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This paper cites Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmis- sion.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmis- sion

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Observation 089d11a3-ebf9-4da6-bb1f-4d265726950e · outbound

This paper cites Interpretable machine learning for precision cognitive aging.Frontiers in Computational Neuroscience, 19:1560064, 2025.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Interpretable machine learning for precision cognitive aging.Frontiers in Computational Neuroscience, 19:1560064, 2025

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.157746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 65b762ee-04da-4218-93d5-a71d1f69c3a2 · outbound

This paper cites Rand hrs longitudinal file 2022 (v1), May 2025.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Rand hrs longitudinal file 2022 (v1), May 2025

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.146846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3b5d65bc-84b2-46e1-941a-3ef3be7e48f7 · outbound

This paper cites Health and retirement study, rand hrs longitudinal file 2022 (v1) public use dataset, 2025.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Health and retirement study, rand hrs longitudinal file 2022 (v1) public use dataset, 2025

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.135115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8b0503fe-290a-46a0-83e4-f1bb06cea109 · outbound

This paper cites URL https://hrsdata.isr.umich.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline URL https://hrsdata.isr.umich

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.124566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation af9b9a4a-2100-43a6-88ef-8a2b23771a07 · outbound

This paper cites Fisher, and A.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Fisher, and A

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.114026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1877928d-2989-4881-979d-f2e1721ee20f · outbound

This paper cites Elias, Alexa Beiser, Philip A.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Elias, Alexa Beiser, Philip A

Reference 52

Resolution: verified exact; doi, observed 2026-08-05T10:39:06.394754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ec5f5a4e-f9ed-48ac-b097-898ac506652c · outbound

This paper cites Laukka, and Brent J.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Laukka, and Brent J

Reference 53

Resolution: verified exact; doi, observed 2026-08-05T10:39:06.141592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7c85b793-faa9-4f02-8022-636bd3a6bbe8 · outbound

This paper cites Langa, David R.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Langa, David R

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.103005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 561bb528-7e59-433a-9540-b5c6dfc1a276 · outbound

This paper cites Langa, David R.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Langa, David R

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.080435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation faf3a5ef-a7df-4171-8a3c-2bd82983a463 · outbound

This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T10:39:04.701503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3162e3cf-7bed-40f5-8d53-acbf3095ca17 · outbound

This paper cites Alzheimer’s Disease Neuroimaging Initiative (ADNI), 2024.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Alzheimer’s Disease Neuroimaging Initiative (ADNI), 2024

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.067595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 34069ff1-9186-4a82-b1dc-929fd54b1fe4 · outbound

This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 58

Resolution: unresolved; raw_fallback, observed 2026-08-05T10:39:08.054523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c5c06619-156a-43a6-ad85-ce7139703904 · outbound

This paper cites Hammers, Kevin Duff, Kelsey R.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Hammers, Kevin Duff, Kelsey R

Reference 59

Resolution: malformed identifier; raw_fallback, observed 2026-08-05T10:39:07.042824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation daba6f8a-9cdb-40d2-b39e-f5192ce6e8ed · outbound

This paper cites Webb, Yiyi Ou, Tatiana Wilkinson, Andrew M.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Webb, Yiyi Ou, Tatiana Wilkinson, Andrew M

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.043543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1c227a31-4d2d-41d0-92f8-1ceaeb164dd5 · outbound

This paper cites Hurd, Paco Martorell, Adeline Delavande, Kathleen J.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Hurd, Paco Martorell, Adeline Delavande, Kathleen J

Reference 61

Resolution: verified exact; doi, observed 2026-08-05T10:39:05.659125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ab8cf428-8156-419b-94c7-6f9ee8321ff6 · outbound

This paper cites Hard negatives were defined as individuals who never had a visit with a worse diagnostic/classification state than their baseline state.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Hard negatives were defined as individuals who never had a visit with a worse diagnostic/classification state than their baseline state

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.031457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 28dfce15-862b-4c79-950f-e94c662f8005 · outbound

This paper cites Positive cases not flagged before transition contributed zero reward.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Positive cases not flagged before transition contributed zero reward

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:39:08.019971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dfe5d3ed-96f0-462e-b382-eacdd1dc905c · outbound

This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-05T10:39:08.008470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5e7a3550-01a2-4d9c-853b-600b94524ac3 · outbound

This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-05T10:39:07.998565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ed8ea7d3-278a-40af-bbd8-021a5f6fb40f · outbound

This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-05T10:39:08.091643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6d835009-b49f-429b-af7a-d5945ec11ec8 · outbound

This paper cites an unresolved cited work.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline Unresolved cited work

Reference 2022

Resolution: verified exact; doi, observed 2026-08-05T10:39:05.883558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 39356a56-ce57-4a37-82a4-9f80b5d5298d · outbound

This paper cites URLhttps://doi.org/10.1098/rsif.2023.0682.

From population norms to personalized trajectories: interpretable Bayesian forecasting for cognitive decline URLhttps://doi.org/10.1098/rsif.2023.0682

Reference 5689

Resolution: verified exact; raw_fallback, observed 2026-08-05T10:39:07.811642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Reference resolution

Outbound references

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