ArticleNeuroscience informatics2022
Gradient boosting decision-tree-based algorithm with neuroimaging for personalized treatment in depression.
Article in Neuroscience informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 17 citations in OpenAlex.
- Obesity-related differences in amygdala and hippocampal volume and metabolism before and after a placebo-controlled antidepressant trial in major depressive disorder.Scientific reports · 2026Trial
- Fatigue in major depression is linked to depression severity, not sleep duration or anterior cingulate cortex neurochemistry.Journal of affective disorders · 2026Article
- Predicting the risk of mental disorders using complete blood count indicators: a machine learning approach.Frontiers in medicine · 2026Article
- Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging.Frontiers in human neuroscience · 2025Article
- Predicting adolescent psychopathology from early life factors: A machine learning tutorial.Global epidemiology · 2024Article
- Article
- Circadian rhythm biomarker from wearable device data is related to concurrent antidepressant treatment response.NPJ digital medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
Introduction: Pretreatment positron emission tomography (PET) with 2-deoxy-2-[ Methods: This study used simultaneous PET/MRS neuroimaging from a double-blind, placebo-controlled, randomized antidepressant trial on 60 participants with major depressive disorder (MDD) before initiating treatment. After eight weeks of treatment, those with ≤ 7 on 17-item Hamilton Depression Rating Scale were designated Results: In test data, the model showed 62% sensitivity, 92% specificity, and 77% weighted accuracy. Pretreatment metabolism of left hippocampus from PET was the most predictive of remission. Conclusions: The pretreatment neuroimaging takes around 60 minutes but has potential to prevent weeks of failed treatment trials. This study effectively addresses common issues for neuroimaging analysis, such as small sample size, high dimensionality, and class imbalance.
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What OpenQuestion 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 OpenQuestion graph.