Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.

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

8 citing papers in PubMed.

1. Systemic lupus in the era of machine learning medicine.Lupus science & medicine · 2024
   Review
2. ClearF++: Improved Supervised Feature Scoring Using Feature Clustering in Class-Wise Embedding and Reconstruction.Bioengineering (Basel, Switzerland) · 2023
   Article
3. A network-based approach reveals long non-coding RNAs associated with disease activity in lupus nephritis: key pathways for flare and potential biomarkers to be used as liquid biopsies.Frontiers in immunology · 2023
   Article
4. Distinct molecular subtypes of systemic sclerosis and gene signature with diagnostic capability.Frontiers in immunology · 2023
   Article
5. What makes a good prediction? Feature importance and beginning to open the black box of machine learning in genetics.Human genetics · 2022
   Review
6. Scaling tree-based automated machine learning to biomedical big data with a feature set selector.Bioinformatics (Oxford, England) · 2020
   Article
7. Approaching neural net feature interpretation using stacked autoencoders: gene expression profiling of systemic lupus erythematosus patients.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019
   Article
8. Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018
   Article

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

5 authors.

Funding

Abstract

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