Leveraging Subjective Parameters and Biomarkers in Machine Learning Models: The Feasibility of

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

2 citing papers in PubMed.

1. Cardiopulmonary Exercise Testing and Quantitative Chest CT in COPD: The Stronger Association of Emphysema Over Airway Thickness with Functional Impairment.International journal of chronic obstructive pulmonary disease · 2026
   Article
2. Development and validation of a multimodal clinical-radiomics-deep learning nomogram based on automated chest CT segmentation for classifying COPD severity: a multicenter study.Frontiers in medicine · 2026
   Article

Corrections and comments

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Authors and funding

14 authors.

Funding

Abstract

PubMed holds no abstract for this paper.

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