Correction to: Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data.

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 synthesis or guideline pooled it.

1. Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review.Journal of medical Internet research · 2021
   Pooled it
2. A Gratifying Step forward for the Application of Artificial Intelligence in the Field of Endoscopy: A Narrative Review.Surgical laparoscopy, endoscopy & percutaneous techniques · 2020
   Review

Corrections and comments

• Erratum for
  Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data.2017

Authors and funding

7 authors.

Funding

Abstract