Question · asked by 1 review
Study-specific random forest classifier vs Caries versus healthy disease-state labels: Study-specific disease-state discrimination
- Population
- Oral microbiome samples in 15 case-controlled studies
- Intervention
- Study-specific random forest classifier
- Comparison
- Caries versus healthy disease-state labels
- Outcome
- Study-specific disease-state discrimination
Bong-Soo 2017, Zhu 2018, and Jiang 2019 had mean AUC scores over 0.75; exact study-specific AUCs were not reported in text or readable figure labels.
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Study-specific random forest classifier vs Caries versus healthy disease-state labels Study-specific disease-state discrimination · Oral microbiome samples in 15 case-controlled studies · Human oral samples Bong-Soo 2017, Zhu 2018, and Jiang 2019 had mean AUC scores over 0.75; exact study-specific AUCs were not reported in text or readable figure labels. Meta-analysis of caries microbiome studies can improve upon disease prediction outcomes. (2022) All outcomes | no estimate extracted | 15 studies | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Meta-analysis of caries microbiome studies can improve upon disease prediction outcomes. 2022 All outcomes | Not specified (studies published from 2012 onward included; no explicit search date reported) | 16 | Not applicable |
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.