Evidence map›Paper›PMID 38324244›Full record

ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2024

Artificial Intelligence and Technology Collaboratories: Innovating aging research and Alzheimer's care.

Peter Abadir, Esther Oh, Rama Chellappa, Niteesh Choudhry, George Demiris, Deepak Ganesan, Jason Karlawish, Benjamin Marlin, Rose M Li, Najim Dehak and 10 more

Open access · hybridAbstract read
In one paragraph

Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. A strategic pathway for the ethical development of AI tools in dementia care.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  3. Article
  4. Reconstructing cerebral lymphatic clearance: an emerging target in the Alzheimer's disease therapeutic pipeline.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Artificial Intelligence and Technology Collaboratories: Innovating aging research and Alzheimer's care.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors at 8 institutions in 1 country.

Peter AbadirJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Esther OhJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Rama ChellappaWhiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Niteesh ChoudhryHarvard Medical School, Harvard University, and Department of Medicine Brigham and Women's Hospital, Boston, Massachusetts, USA.
George DemirisSchool of Nursing, University of Pennsylvania, and Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Deepak GanesanManning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, Massachusetts, USA.
Jason KarlawishPerelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Benjamin MarlinManning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, Massachusetts, USA.
Rose M LiRose Li and Associates, Inc., Chevy Chase, Maryland, USA.
Najim DehakWhiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Alicia ArbajeJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Mathias UnberathWhiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Thomas CudjoeJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Christopher ChuteJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Jason H MooreDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Phillip PhanJohns Hopkins Carey Business School, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Quincy SamusJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Nancy L SchoenbornJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Alexis BattleWhiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Jeremy D WalstonJohns Hopkins Medicine, Johns Hopkins University, School of Medicine, Baltimore, Maryland, USA.
Johns Hopkins University · USJohns Hopkins Medicine · USUniversity of Pennsylvania · USAmherst College · USBrigham and Women's Hospital · USCedars-Sinai Medical Center · USShort and Associates (United States) · USUniversity of Massachusetts Amherst · US

Funding

Validating novel sleep sensors and devices in older adults with Alzheimer's diseaseP30AG073107 · NIA · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Sudeshna Das · 2021 to 2026
$32.0M
Utilizing Technology and AI Approaches to Facilitate Independence andResilience in Older AdultsP30AG073104 · NIA · JOHNS HOPKINS UNIVERSITY · PI Peter M. Abadir, Alexis Battle · 2021 to 2026
$31.2M
Research Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI MARILYN S. ALBERT · 2020 to 2026
$29.3M
Research Education ComponentP30AG072979 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVID A WOLK · 2021 to 2026
$24.8M
Technology Identification and Training CoreP30AG073105 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DEMIRIS, GEORGE, KARLAWISH, JASON H · 2021 to 2025
$21.2M
AI + Aging (a2) Coordinating Center for the NIA Artificial Intelligence and Technology Collaboratories for Aging Research (AITCs)U24AG073094 · NIA · ROSE LI AND ASSOCIATES, INC. · PI LEE, ALBERT, LI, ROSE MARIA · 2021 to 2025
$5.1M
NIA NIH HHS P30 AG066507NIA NIH HHS P30 AG072979NIA NIH HHS P30 AG073104NIA NIH HHS P30 AG073105NIA NIH HHS P30 AG073107NIA NIH HHS U24 AG073094
6 · The paper itself

Abstract

This perspective outlines the Artificial Intelligence and Technology Collaboratories (AITC) at Johns Hopkins University, University of Pennsylvania, and University of Massachusetts, highlighting their roles in developing AI-based technologies for older adult care, particularly targeting Alzheimer's disease (AD). These National Institute on Aging (NIA) centers foster collaboration among clinicians, gerontologists, ethicists, business professionals, and engineers to create AI solutions. Key activities include identifying technology needs, stakeholder engagement, training, mentoring, data integration, and navigating ethical challenges. The objective is to apply these innovations effectively in real-world scenarios, including in rural settings. In addition, the AITC focuses on developing best practices for AI application in the care of older adults, facilitating pilot studies, and addressing ethical concerns related to technology development for older adults with cognitive impairment, with the ultimate aim of improving the lives of older adults and their caregivers. HIGHLIGHTS: Addressing the complex needs of older adults with Alzheimer's disease (AD) requires a comprehensive approach, integrating medical and social support. Current gaps in training, techniques, tools, and expertise hinder uniform access across communities and health care settings. Artificial intelligence (AI) and digital technologies hold promise in transforming care for this demographic. Yet, transitioning these innovations from concept to marketable products presents significant challenges, often stalling promising advancements in the developmental phase. The Artificial Intelligence and Technology Collaboratories (AITC) program, funded by the National Institute on Aging (NIA), presents a viable model. These Collaboratories foster the development and implementation of AI methods and technologies through projects aimed at improving care for older Americans, particularly those with AD, and promote the sharing of best practices in AI and technology integration. Why Does This Matter? The National Institute on Aging (NIA) Artificial Intelligence and Technology Collaboratories (AITC) program's mission is to accelerate the adoption of artificial intelligence (AI) and new technologies for the betterment of older adults, especially those with dementia. By bridging scientific and technological expertise, fostering clinical and industry partnerships, and enhancing the sharing of best practices, this program can significantly improve the health and quality of life for older adults with Alzheimer's disease (AD).

Indexed as

Alzheimer DiseaseIsothiocyanatesAgedArtificial IntelligenceGeroscienceHumansQuality of LifeTechnologyUnited States2,3,4-tri-O-acetylarabinopyranosyl isothiocyanateIsothiocyanatesAlzheimer's diseaseartificial intelligencehealthy agingmachine learningolder adultspilot studiestechnology

Identifiers

PMID38324244
PMCPMC11032553
OpenAlexW4391617127

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.