A Novel Preoperative Prediction Model Based on Deep Learning to Predict Neoplasm T Staging and Grading in Patients with Upper Tract Urothelial Carcinoma.

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

3 citing papers in PubMed.

1. Beyond diagnosis: exploring the extended clinical utility of urine fluorescence in situ hybridization in upper tract urothelial carcinoma.BMC urology · 2025
   Article
2. Imaging in Upper Tract Urothelial Carcinoma: A Review.Cancers · 2023
   Review
3. The combined deep learning model integrating CT features and clinical variables for preoperative T-stage diagnosis in esophageal cancer: A multicenter study.Digital health
   Article

Corrections and comments

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Authors and funding

8 authors.

Funding

Abstract

PubMed holds no abstract for this paper.

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