ArticleCancers2021
Deep Learning Prediction of Metastasis in Locally Advanced Colon Cancer Using Binary Histologic Tumor Images.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Surgical treatment of locally advanced right colon cancer invading neighboring organs.Frontiers in medicine · 2022Pooled it
- Deep Spectrogram Learning for Gunshot Classification: A Comparative Study of CNN Architectures and Time-Frequency Representations.Journal of imaging · 2025Article
- A retrospective analysis of key predictors and patient outcomes: Using artificial intelligence for precision survival prediction in colorectal cancer.German medical science : GMS e-journal · 2025Article
- Unselective Measurement of Tumor-to-Stroma Proportion in Colon Cancer at the Invasion Front-An Elusive Prognostic Factor: Original Patient Data and Review of the Literature.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial intelligence and digital biomarker in precision pathology guiding immune therapy selection and precision oncology.Cancer reports (Hoboken, N.J.) · 2023Review
- Multimodal AI for prediction of distant metastasis in carcinoma patients.Frontiers in bioinformatics · 2023Article
- The role of deep learning in diagnosing colorectal cancer.Przeglad gastroenterologiczny · 2023Review
- Article
- Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, we developed the Binary ImaGe Colon Metastasis classifier (BIg-CoMet), a semi-guided approach for the stratification of colon cancer patients into two risk groups for the occurrence of distant metastasis, using an InceptionResNetV2-based deep learning model trained on binary images. We enrolled 291 colon cancer patients with pT3 and pT4 adenocarcinomas and converted one cytokeratin-stained representative tumor section per case into a binary image. Image augmentation and dropout layers were incorporated to avoid overfitting. In a validation collective (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.