Evidence map›Paper›PMID 37654029›Full record

ReviewAlzheimer's & dementia : the journal of the Alzheimer's Association2023

Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia.

Laura M Winchester, Eric L Harshfield, Liu Shi, AmanPreet Badhwar, Ahmad Al Khleifat, Natasha Clarke, Amir Dehsarvi, Imre Lengyel, Ilianna Lourida, Christopher R Madan and 8 more

Abstract readReview
In one paragraph

Review in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

18 authors.

Laura M WinchesterDepartment of Psychiatry, Oxford University, Oxford, UK.
Eric L HarshfieldDepartment of Clinical Neurosciences, Stroke Research Group, University of Cambridge, Cambridge, UK.
Liu ShiNovo Nordisk Research Centre Oxford (NNRCO), Headington, UK.
AmanPreet BadhwarDépartement de Pharmacologie et Physiologie, Institut de Génie Biomédical, Faculté de Médecine, Université de Montréal, Montreal, Canada.
Ahmad Al KhleifatDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Natasha ClarkeCentre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada.
Amir DehsarviSchool of Medicine, Medical Sciences, and Nutrition, University of Aberdeen, Aberdeen, UK.
Imre LengyelWellcome-Wolfson Institute of Experimental Medicine, Queen's University, Belfast, UK.
Ilianna LouridaHealth and Community Sciences, University of Exeter Medical School, Exeter, UK.
Christopher R MadanSchool of Psychology, University of Nottingham, Nottingham, UK.
Sarah J MarziUK Dementia Research Institute at Imperial College London, London, UK.
Petroula ProitsiDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Anto P RajkumarInstitute of Mental Health, Mental Health and Clinical Neurosciences academic unit, University of Nottingham, Nottingham, UK, Mental health services of older people, Nottinghamshire healthcare NHS foundation trust, Nottingham, UK.
Timothy RittmanDepartment of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Edina SilajdžićDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Stefano TamburinDepartment of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
Janice M RansonHealth and Community Sciences, University of Exeter Medical School, Exeter, UK.
David J LlewellynHealth and Community Sciences, University of Exeter Medical School, Exeter, UK.

Funding

Identifying modifiable aspects of gene-by-environment interplay in later-life cognitive declineRF1AG055654 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI FAUL, JESSICA, GALAMA, TITUS JOHANNES · 2017 to 2018
$4.3M
Medical Research Council MR/N029941/1Medical Research Council MR/X005674/1NIA NIH HHS RF1 AG055654
6 · The paper itself

Abstract

With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies. Overcoming these challenges will involve collecting data from underrepresented populations, developing more powerful AI approaches, validating the use of noninvasive biomarkers, and adhering to reporting guidelines. By harnessing rich multimodal data through AI approaches and international collaborative innovation, we are well positioned to identify clinically useful biomarkers that are accurate, generalizable, unbiased, and acceptable in clinical practice. HIGHLIGHTS: Artificial intelligence and machine learning approaches may accelerate dementia biomarker discovery. Remaining challenges include data set suitability due to size and bias in cohort selection. Multimodal data, diverse data sets, improved machine learning approaches, real-world validation, and interdisciplinary collaboration are required.

Indexed as

Alzheimer DiseaseBiomedical ResearchArtificial IntelligenceHumansMachine LearningAIbiomarker discoverydementiamachine learningmultimodal

Identifiers

PMID37654029
PMCPMC10840606

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.