ArticleDiagnostics (Basel, Switzerland)2025
Explainable Machine Learning in the Prediction of Depression.
Article in Diagnostics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed.
- Integrating epidemiologic modeling and explainable machine learning to predict and identify factors associated with self-reported depression among adults in Tennessee, United States.Discover mental health · 2026Article
- Machine learning-based risk classification of depressive symptoms among patients with hearing loss: evidence from the Health and Retirement Study (HRS).Comprehensive psychoneuroendocrinology · 2026Article
- Development and Validation of Machine Learning-Based Models for Predicting Postoperative Depression Risk in Patients With Ovarian Cancer.Actas espanolas de psiquiatria · 2026Article
- Article
- AI competency misalignment in preventive medicine: a multi-stakeholder survey with latent profile analysis in Sichuan and Chongqing.International journal of public health · 2026Article
- Structural determinants of depressive symptoms among refugees and host communities in South Sudan: evidence from explainable machine learning.Frontiers in public health · 2026Article
- An interpretable delta ultrasound radiomics model for predicting live birth outcomes in single vitrified-warmed blastocyst transfer.Journal of ovarian research · 2025Article
- Systematic Review and Meta-Analysis of Explainable Machine Learning Models for Clinical Depression Detection.Behavioral sciences (Basel, Switzerland) · 2025Review
- Explainable AI for Depression Detection and Severity Classification From Activity Data: Development and Evaluation Study of an Interpretable Framework.JMIR mental health · 2025Article
- Explaining factors influencing students' depression with a deep learning approach.Frontiers in psychology · 2025Article
- Integrating explainable AI with clinical features to enhance ADHD diagnostic understanding.Frontiers in psychiatry · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.