Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning | Paper Citation Record

Observation a6c8027c-c82b-43f2-a5a4-85e639b3d462 · outbound

This paper cites Dementia prevention, interven- tion, and care: 2024 report of the lancet standing commission,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Dementia prevention, interven- tion, and care: 2024 report of the lancet standing commission,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 53308282-0607-4902-ba4c-44a8287b27d3 · outbound

This paper cites Dementia,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Dementia,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:12.098735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6bf6281f-f1ab-4f75-b128-6451ca26b607 · outbound

This paper cites Dementia in home and community care,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Dementia in home and community care,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:12.079845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e515fead-f619-4a8a-a27e-696f828f1034 · outbound

This paper cites Agitation and dementia: prevention and treatment strategies in acute and chronic conditions,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Agitation and dementia: prevention and treatment strategies in acute and chronic conditions,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:12.037162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eb98a406-0ae8-4221-8de3-b47faac58a6f · outbound

This paper cites In- stitutionalization risk and costs associated with agitation in alzheimer’s disease,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning In- stitutionalization risk and costs associated with agitation in alzheimer’s disease,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:12.014053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation da1851ab-e954-466e-aaf9-61359f873e85 · outbound

This paper cites The impact of agitation in dementia on caregivers: a real-world survey,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning The impact of agitation in dementia on caregivers: a real-world survey,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.992957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b7d2d178-8e20-4381-998d-c4cab3abceda · outbound

This paper cites Barriers and facilitators to care for agitation and/or aggression among persons living with de- mentia in long-term care,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Barriers and facilitators to care for agitation and/or aggression among persons living with de- mentia in long-term care,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.966861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2fee3d2e-37a1-47ce-9258-94bfd80993af · outbound

This paper cites A novel multi-modal sensor dataset and benchmark to detect agitation in people living with dementia in a residential care setting,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning A novel multi-modal sensor dataset and benchmark to detect agitation in people living with dementia in a residential care setting,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.944104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fc13cf24-c951-41eb-909b-ec4cb9b73451 · outbound

This paper cites Privacy- protecting behaviours of risk detection in people with dementia using videos,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Privacy- protecting behaviours of risk detection in people with dementia using videos,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.925141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f493e8e3-29e8-4d9d-b3b2-9277c24bb765 · outbound

This paper cites Sensor- based agitation prediction in institutionalized people with dementia a systematic review,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Sensor- based agitation prediction in institutionalized people with dementia a systematic review,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.902981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d0362dca-ae1b-40c6-88a3-3e352e9e0337 · outbound

This paper cites Tihm: An open dataset for remote healthcare monitoring in dementia,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Tihm: An open dataset for remote healthcare monitoring in dementia,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.880370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 15a4be4b-bb94-401e-b216-bc08d58106dc · outbound

This paper cites Data-driven forecasting of agitation for persons with dementia: A deep learning-based ap- proach,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Data-driven forecasting of agitation for persons with dementia: A deep learning-based ap- proach,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.860246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 918669c2-e2f1-4e97-8706-a9b687a21887 · outbound

This paper cites Dementiacaregiverexperiencesandrecommendationsforusingthebehavioraland environmental sensing and intervention system at home: usability and acceptability study,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Dementiacaregiverexperiencesandrecommendationsforusingthebehavioraland environmental sensing and intervention system at home: usability and acceptability study,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.829922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cac740dd-34a0-45a6-9a4a-d799990adb00 · outbound

This paper cites Nonpharmacologic management of behavioral symptoms in dementia,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Nonpharmacologic management of behavioral symptoms in dementia,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.800924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ef1bf649-d0d1-4e38-abe6-365691e30b07 · outbound

This paper cites Wristaccelerometryformonitoringdementiaagitationbehaviour in clinical settings: A scoping review,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Wristaccelerometryformonitoringdementiaagitationbehaviour in clinical settings: A scoping review,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.758899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 10b6fd3a-4cfd-425b-991e-809b550fae72 · outbound

This paper cites Available: https://www.cihi.ca/en/dementia-in-canada/ dementia-care-across-the-health-system/dementia-in-home-and-community-care.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Available: https://www.cihi.ca/en/dementia-in-canada/ dementia-care-across-the-health-system/dementia-in-home-and-community-care

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:12.060332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bdd1ebca-8386-4bde-9f1a-f62f97fc7233 · outbound

This paper cites Heart rate variability and risk of agitation in alzheimer’s disease: The atherosclerosis risk in communities study,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Heart rate variability and risk of agitation in alzheimer’s disease: The atherosclerosis risk in communities study,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.626178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c629e537-b50f-42c3-b8fb-eead12f606c8 · outbound

This paper cites Association between blood pressure variability with dementia and cognitive impairment: a systematic review and meta-analysis,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Association between blood pressure variability with dementia and cognitive impairment: a systematic review and meta-analysis,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.485133Z

Source-reported events for the cited work

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Observation 533f0a21-189c-419e-a82a-4de362ede13a · outbound

This paper cites Sleep and agitation in nursing home residents with and without dementia,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Sleep and agitation in nursing home residents with and without dementia,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.399037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3d9a1fdf-7f7d-4b55-8289-d79402c147db · outbound

This paper cites Wearable multimodal sensors for the detection of behav- ioral and psychological symptoms of dementia using personalized machine learning models,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Wearable multimodal sensors for the detection of behav- ioral and psychological symptoms of dementia using personalized machine learning models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.291353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 74d523a8-785a-425a-ab2f-66a1fac7f307 · outbound

This paper cites Artificial intelligence-driven virtual rehabilitation for people living in the community: A scoping review,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Artificial intelligence-driven virtual rehabilitation for people living in the community: A scoping review,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.209694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bf9f0ce9-e1ed-4cb0-8701-86b0db4386cf · outbound

This paper cites Maison-multimodal ai-based sensor platform for older individuals,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Maison-multimodal ai-based sensor platform for older individuals,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.119488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d84e4322-5ad0-4c91-afd6-69e1ffa02274 · outbound

This paper cites Applications and outcomes of internet of things for patients with alzheimer’s disease/dementia: A scoping review,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Applications and outcomes of internet of things for patients with alzheimer’s disease/dementia: A scoping review,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:11.013818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cdc002e9-3c6c-4a59-ae76-78fb64597dd3 · outbound

This paper cites Detecting agitation and aggres- sion in people with dementia using sensors—a systematic review,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Detecting agitation and aggres- sion in people with dementia using sensors—a systematic review,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.896556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 65ab170d-89d9-4086-a922-ad121b52bb6e · outbound

This paper cites Healthcare evolves from reactive to proactive,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Healthcare evolves from reactive to proactive,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.803892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation db604c87-1b1f-43d2-bda2-2316979fe703 · outbound

This paper cites Multidimensional assessment of challenging behaviors in advanced stages of dementia in nursing homes—the insidedem framework,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Multidimensional assessment of challenging behaviors in advanced stages of dementia in nursing homes—the insidedem framework,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.661878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 35eed8ca-8f4e-43fd-92ef-0a94e3382ff2 · outbound

This paper cites Methodology for establishing a community- wide life laboratory for capturing unobtrusive and continuous remote activity and health data,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Methodology for establishing a community- wide life laboratory for capturing unobtrusive and continuous remote activity and health data,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.539327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 351b9775-2fb4-4f42-bd5c-71303b7ad612 · outbound

This paper cites Daad: A framework for detecting agitation and aggression in people living with dementia using a novel multi-modal sensor network,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Daad: A framework for detecting agitation and aggression in people living with dementia using a novel multi-modal sensor network,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.406715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad1ab1ff-3afa-4abb-9fce-0048f7be0cba · outbound

This paper cites Agitation detection in people living with dementia using multimodal sensors,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Agitation detection in people living with dementia using multimodal sensors,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.270505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 484e8bd2-30d9-431a-b536-e60992abc470 · outbound

This paper cites A pilot study to detect agitation in people living with dementia using multi-modal sensors,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning A pilot study to detect agitation in people living with dementia using multi-modal sensors,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.135690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 34d6e5df-bc2b-49c4-859f-500d4e30f060 · outbound

This paper cites Undersampling and cumulative class re-decision methods to improve detection of agitation in people with dementia,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Undersampling and cumulative class re-decision methods to improve detection of agitation in people with dementia,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:10.009035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b7079a95-3a68-42f8-ad4c-24440daf5357 · outbound

This paper cites Dave: detecting agitated vocal events,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Dave: detecting agitated vocal events,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:09.825196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d8cf5e3b-4923-4d95-83f9-4c980c2cba6a · outbound

This paper cites Semi-supervised Learning for Identifying the Likelihood of Agitation in People with Dementia.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Semi-supervised Learning for Identifying the Likelihood of Agitation in People with Dementia

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:34:07.732969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4345c059-69f6-4d81-a44d-799cebbaba04 · outbound

This paper cites Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:34:07.546938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68c942c7-8566-4dac-88ee-5cc5f41a7392 · outbound

This paper cites Prediction of Dementia-related Agitation Using Multivariate Ambient Environmental Time-series Data.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Prediction of Dementia-related Agitation Using Multivariate Ambient Environmental Time-series Data

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:34:07.339291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a7cf222d-f9fe-403f-8f52-d9c49cf60b77 · outbound

This paper cites Sundowning in dementia: clinical relevance, patho- physiological determinants, and therapeutic approaches,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Sundowning in dementia: clinical relevance, patho- physiological determinants, and therapeutic approaches,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:09.678779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2dc1ae6f-66e7-4442-926b-9da6d251ede3 · outbound

This paper cites The proportion of missing data should not be used to guide decisions on multiple imputation,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning The proportion of missing data should not be used to guide decisions on multiple imputation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:09.501089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a5005cb2-cf88-4ab1-826f-5c506a967ad4 · outbound

This paper cites Junaid, T.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Junaid, T

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:09.350865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 002f893f-ce76-4aa5-b9e6-582a33c00f93 · outbound

This paper cites Rak-Areekul, Y.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Rak-Areekul, Y

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:09.249789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 084f8262-e8fb-44c5-a154-ea5fd5ee22a7 · outbound

This paper cites “sundowning.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning “sundowning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:09.087399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4293d7ec-fa37-4eff-8137-4bc97c15b64b · outbound

This paper cites Temporal patterns of agitation in dementia,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Temporal patterns of agitation in dementia,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:08.997496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 63b38276-fc52-4633-b4b7-d89d4cbb31b9 · outbound

This paper cites Unsupervised deep learning to detect agitation from videos in people with dementia,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Unsupervised deep learning to detect agitation from videos in people with dementia,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:08.860996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c3831f9f-50b0-4639-9295-e4efb6ea8ccc · outbound

This paper cites Accurate predictions on small data with a tabular foundation model,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Accurate predictions on small data with a tabular foundation model,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:06.094162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 141a8188-0ab5-4904-9e7c-5b5e05521a52 · outbound

This paper cites Greedy function approximation: a gradient boosting machine,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Greedy function approximation: a gradient boosting machine,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:06.206086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00428da0-449a-4a81-93fa-d2e84b63417a · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Lightgbm: A highly efficient gradient boosting decision tree,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T14:34:06.300516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f3ef866-6faf-4640-8c26-25cc8089b188 · outbound

This paper cites Comparison of naive bayes, random for- est, decision tree, support vector machines, and logistic regression classifiers for text reviews classification,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Comparison of naive bayes, random for- est, decision tree, support vector machines, and logistic regression classifiers for text reviews classification,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:08.694933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 73e1e43c-44d6-4d63-aa95-0724e5132022 · outbound

This paper cites Attention is all you need,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Attention is all you need,

Reference 47

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Observation ee5bbecf-1063-4269-a6c5-f9da61ed7cc3 · outbound

This paper cites Rocket:exceptionallyfastandaccurate time series classification using random convolutional kernels,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Rocket:exceptionallyfastandaccurate time series classification using random convolutional kernels,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:08.533800Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f8164327-41c0-492e-8d9a-bc57750cd177 · outbound

This paper cites One-class classification with node embedding type fea- tures,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning One-class classification with node embedding type fea- tures,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:08.397324Z

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Observation cac7e5bf-ad54-4bb0-8305-b576e2a97a74 · outbound

This paper cites Class-balanced loss based on effective number of samples,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Class-balanced loss based on effective number of samples,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:08.280960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 35d67043-a013-4769-85da-363da1df5421 · outbound

This paper cites Smote: syn- thetic minority over-sampling technique,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Smote: syn- thetic minority over-sampling technique,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:08.035094Z

Source-reported events for the cited work

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Observation 87005508-1751-42b6-a642-29f27c73ac5f · outbound

This paper cites A unified approach to interpreting model predic- tions,.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning A unified approach to interpreting model predic- tions,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:34:07.862390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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