Evidence map›Paper›PMID 40398391›Full record

ReviewCell reports. Medicine2025

AI-powered integration of multimodal imaging in precision medicine for neuropsychiatric disorders.

Weijie Huang, Ni Shu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cell reports. Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Review
  19. Review
  20. Review
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

2 authors.

Weijie HuangCollege of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, MOE Key Laboratory of Brain Computer Intelligence Technology, Nanjing 211106, China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; BABRI Centre, Beijing Normal University, Beijing 100875, China.
Ni ShuState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; BABRI Centre, Beijing Normal University, Beijing 100875, China. Electronic address: nshu@bnu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuropsychiatric disorders have complex pathological mechanism, pronounced clinical heterogeneity, and a prolonged preclinical phase, which presents a challenge for early diagnosis and development of precise intervention strategies. With the development of large-scale multimodal neuroimaging datasets and advancement of artificial intelligence (AI) algorithms, the integration of multimodal imaging with AI techniques has emerged as a pivotal avenue for early detection and tailoring individualized treatment for neuropsychiatric disorders. To support these advances, in this review, we outline multimodal neuroimaging techniques, AI methods, and strategies for multimodal data fusion. We highlight applications of multimodal AI based on neuroimaging data in precision medicine for neuropsychiatric disorders, discussing challenges in clinical adoption, their emerging solutions, and future directions.

Indexed as

Artificial IntelligenceMental DisordersMultimodal ImagingNeuroimagingPrecision MedicineHumansalgorithmic biasartificial intelligencedata privacydiagnostic modelsdisorder managementmagnetic resonance imagingmultimodality fusionneuroimagingneuropsychiatric disorderspatient stratificationpositron emission tomographyprecision medicineprognostic modelsupervised learning

Identifiers

PMID40398391
PMCPMC12147894

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.