Evidence map›Paper›PMID 42761863›Full record

Article...IEEE...International Conference on Connected Health: Applications, Systems and Engineering Technologies. IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies2026

Optimizing Symptom Surveys with Machine Learning to Predict PTSD One Year Post-trauma.

Charles Prince, Hong Xie, Stephen Grider, Xin Wang, Kevin S Xu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ...IEEE...International Conference on Connected Health: Applications, Systems and Engineering Technologies. IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Charles PrinceCase Western Reserve University, Cleveland, OH 44106 USA.
Hong XieUniversity of Toledo, Toledo, OH 43614 USA.
Stephen GriderUniversity of Toledo, Toledo, OH 43614 USA.
Xin WangUniversity of Toledo, Toledo, OH 43614 USA.
Kevin S XuCase Western Reserve University, Cleveland, OH 44106 USA.

Funding

Study of early brain alterations that predict development of chronic PTSDR01MH110483 · NIMH · UNIVERSITY OF TOLEDO HEALTH SCI CAMPUS · PI WANG, XIN · 2016 to 2021
$3.8M
A large sample machine learning network analysis of vertex cortical thickness measures for high resolution definition of PTSD related cortical structure abnormalitiesR21MH125277 · NIMH · UNIVERSITY OF TOLEDO HEALTH SCI CAMPUS · PI WANG, XIN · 2022 to 2023
$412k
NIMH NIH HHS R01 MH110483NIMH NIH HHS R21 MH125277
6 · The paper itself

Abstract

Post-traumatic stress disorder (PTSD), a lasting mental health disorder, can be a burden to monitor for patients and clinicians. This work introduces AI-driven methods to understand the predictive value of behavioral symptom surveys for PTSD diagnosis one year post-trauma. We find that surveys issued at regular time intervals can predict PTSD diagnosis with moderate accuracy of around 75% (AUC

Indexed as

adaptive diagnosisfeature selectionPost-traumatic stress disordersurvey minimization

Identifiers

PMID42761863
PMCPMC13587745

What OpenQuestion holds

Textmetadata
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.