From research to clinical practice: Expert consensus on Neuroimaging AI tools for the Memory clinic (Neuro-AIM)

Abstract Although AI tools for neuroimaging show considerable promise in the diagnosis, prognosis, and management of neurodegenerative disorders, their uptake in memory clinics has been limited. A key barrier is lack of consensus on their effective design and implementation. Here we establish expert consensus on the specific goals, usage and challenges of AI tools for neuroimaging in the memory clinic using a Delphi process. Sixteen experts from clinical, academic, and industry backgrounds participated in three rounds of questionnaires, coordinated by the Imaging Working Group of the Deep Dementia Phenotyping (DEMON) network, with support from a patient and public involvement representative. Consensus was reached on eight statements covering four themes: purpose, quality, interactions with clinicians and memory clinics, and privacy and ethics. Implementation of these recommendations will further the adoption of AI neuroimaging tools from research to clinical practice, improving diagnostic and care pathways for patient benefit.

Authors

Institutions

Publication Details

Journal
npj Digital Medicine
Published
2026-10-14
DOI
https://doi.org/10.1038/s41746-026-03296-9
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From research to clinical practice: Expert consensus on Neuroimaging AI tools for the Memory clinic (Neuro-AIM)

Meike Willemijn Vernooij, Geert Vanhooren, Timothy Rittman, Mathias Huybrechts et al.
npj Digital Medicine
Dementia and Cognitive Impairment Research
article

From research to clinical practice: Expert consensus on Neuroimaging AI tools for the Memory clinic (Neuro-AIM)

Meike Willemijn Vernooij, Geert Vanhooren, Timothy Rittman, Mathias Huybrechts, Rose Bruffaerts, Usman Saeed, Stefano Tamburin, Catherine J Scott, Angela Tam, Jay Amin, Matthew Leming, Jennifer Camaradou, David J. Llewellyn, Dirk Smeets, Lewis Hotchkiss, Natasha Clarke, James Leighs
article en

Abstract

Abstract Although AI tools for neuroimaging show considerable promise in the diagnosis, prognosis, and management of neurodegenerative disorders, their uptake in memory clinics has been limited. A key barrier is lack of consensus on their effective design and implementation. Here we establish expert consensus on the specific goals, usage and challenges of AI tools for neuroimaging in the memory clinic using a Delphi process. Sixteen experts from clinical, academic, and industry backgrounds participated in three rounds of questionnaires, coordinated by the Imaging Working Group of the Deep Dementia Phenotyping (DEMON) network, with support from a patient and public involvement representative. Consensus was reached on eight statements covering four themes: purpose, quality, interactions with clinicians and memory clinics, and privacy and ethics. Implementation of these recommendations will further the adoption of AI neuroimaging tools from research to clinical practice, improving diagnostic and care pathways for patient benefit.

npj Digital Medicine
University of Verona (IT), University College London Hospitals NHS Foundation Trust (GB), Vrije Universiteit Brussel (BE), University of Antwerp (BE), University of Toronto (CA), University of Exeter (GB), University of Cambridge (GB), Erasmus MC (NL), Swansea University (GB), Massachusetts General Hospital (US), Antwerp University Hospital (BE), AZ Sint-Jan (BE), Institut Universitaire de Gériatrie de Montréal (CA), Center for Systems Biology (US), Icometrix (Belgium) (BE), University of Southampton (GB), Sunnybrook Research Institute, UCL Queen Square Institute of Neurology (GB), University College London (GB), Université de Montréal (CA), Hasselt University (BE)
Massachusetts General Hospital, Sunnybrook Research Institute, National Institute for Health and Care Research, Department of Health and Social Care, University of Exeter, University of Southampton, University College London, Swansea University, Alzheimer’s Research UK, Vrije Universiteit Brussel, Université de Montréal, Università degli Studi di Verona, Universiteit Antwerpen, University College London Hospitals NHS Foundation Trust, Universiteit Hasselt, NIHR Cambridge Biomedical Research Centre, Temerty Faculty of Medicine, University of Toronto
Good health and well-being
Openalex Percentile: Top 13%
Dementia and Cognitive Impairment Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.