Unique Microbial Characterisation of Oesophageal Squamous Cell Carcinoma Patients with Different Dietary Habits Based on Light Gradient Boosting Machine Learning Classifier.

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

4 citing papers in PubMed.

1. Development and validation of prediction model for intrapulmonary metastasis in lung adenocarcinoma based on machine learning.Journal of thoracic disease · 2026
   Article
2. A machine learning integrated multi-omics framework for risk prediction and target discovery in insomnia aggravated sepsis induced acute lung injury.Frontiers in immunology · 2026
   Article
3. Plant-based diet quality is associated with esophageal mucosa-associated microbiome profiles and disease severity in a high-risk Chinese population.Journal of oral microbiology · 2026
   Article
4. AI-driven pathology in esophageal cancer: from early screening to precision prognostics.Frontiers in oncology · 2026
   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

6 authors.

Funding

Abstract

PubMed holds no abstract for this paper.

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