Predicting potential lncRNA biomarkers for lung cancer and neuroblastoma based on an ensemble of a deep neural network and LightGBM.

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

5 citing papers in PubMed, 4 citations in OpenAlex.

1. Deep Learning-Based Analysis of Gene Expression Data and Gene-Related Information in Pediatric Surgical Oncology: A Scoping Review.Cancer medicine · 2026
   Article
2. Unveiling the molecular landscape: Long non-coding RNAs in neuroblastoma (Review).Oncology reports · 2026
   Review
3. LDA-SCGB: inferring lncRNA-disease associations based on condensed gradient boosting.BMC bioinformatics · 2025
   Article
4. A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025
   Review
5. Artificial intelligence in lung cancer: current applications, future perspectives, and challenges.Frontiers in oncology · 2024
   Review

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 at 5 institutions in 1 country.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.

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