A TabNet-Based Multidimensional Deep Learning Model for Predicting Doxorubicin-Induced Cardiotoxicity in Breast Cancer 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

3 citing papers in PubMed.

1. Machine learning-enhanced baseline risk prediction models for cancer therapy related cardiac dysfunction: a systematic review and critical appraisal of methodological quality.European heart journal. Digital health · 2026
   Article
2. Virtual reality for pain and anxiety reduction during venous puncture procedures : A within-subject clinical crossover study.Wiener klinische Wochenschrift · 2026
   Article
3. Development and external validation of an interpretable deep learning model for early immune-related adverse events in hepatocellular carcinoma.Frontiers in immunology · 2026
   Article

Corrections and comments

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Authors and funding

5 authors.

Funding

Abstract

PubMed holds no abstract for this paper.

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