ArticleTheranostics2020
Real-time colorectal cancer diagnosis using PR-OCT with deep learning.
Article in Theranostics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed, 1 synthesis or guideline pooled it, 60 citations in OpenAlex.
- Visualizing knowledge evolution trends and research hotspots of artificial intelligence in colorectal cancer: A bibliometric analysis.Frontiers in oncology · 2022Pooled it
- Dual-resolution megahertz optical coherence tomography prototype rectoscope for enhanced visualization of colorectal microstructures.Journal of biomedical optics · 2026Article
- Three-dimensional ex-vivo visualization of normal and inflamed small intestine and colonic tissue using optical coherence tomography.Scientific reports · 2026Article
- Translational artificial intelligence in gastrointestinal and hepatic disorders: Advancing intelligent clinical decision-making for diagnosis, treatment, and prognosis.World journal of gastroenterology · 2025Review
- Classification of colon polyps with malignant potential using statistical analysis of features extracted from ex vivo optical coherence tomography images.Biomedical engineering online · 2025Article
- A novel approach for estimating postmortem intervals under varying temperature conditions using pathology images and artificial intelligence models.International journal of legal medicine · 2025Article
- Deep learning for the detection of colon polyps with malignant potential: ex vivo classification using feature-enhanced optical coherence tomography (OCT) images.Biomedical optics express · 2025Article
- AI-Powered Clinical Decision Support Systems in Disease Diagnosis, Treatment Planning, and Prognosis: A Systematic Review.Medical journal of the Islamic Republic of Iran · 2025Review
- Advancements in real-time oncology diagnosis: harnessing AI and image fusion techniques.Frontiers in oncology · 2025Review
- In vivo evaluation of complex polyps with endoscopic optical coherence tomography and deep learning during routine colonoscopy: a feasibility study.Scientific reports · 2024Article
- Molecular Imaging Biomarkers for Early Cancer Detection: A Systematic Review of Emerging Technologies and Clinical Applications.Diagnostics (Basel, Switzerland) · 2024Review
- Deep learning classification of ex vivo human colon tissues using spectroscopic optical coherence tomography.Journal of biophotonics · 2024Article
- Tissue Elasticity as a Diagnostic Marker of Molecular Mutations in Morphologically Heterogeneous Colorectal Cancer.International journal of molecular sciences · 2024Article
- High-resolution rectoscopy using MHz optical coherence tomography: a step towards real time 3D endoscopy.Scientific reports · 2024Article
- Article
- The LMIT: Light-mediated minimally-invasive theranostics in oncology.Theranostics · 2024Review
- Optical coherence tomography combined with convolutional neural networks can differentiate between intrahepatic cholangiocarcinoma and liver parenchyma ex vivo.Journal of cancer research and clinical oncology · 2023Article
- Optical coherence tomography and convolutional neural networks can differentiate colorectal liver metastases from liver parenchyma ex vivo.Journal of cancer research and clinical oncology · 2023Article
- The role of deep learning in diagnosing colorectal cancer.Przeglad gastroenterologiczny · 2023Review
- Towards targeted colorectal cancer biopsy based on tissue morphology assessment by compression optical coherence elastography.Frontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering an alternative technique to endoscopic biopsy - the current gold-standard colorectal cancer screening and surveillance modality. To help clinical translation limited by processing the large volume of generated data, we designed a deep learning-based pattern recognition (PR) OCT system that automates image processing and provides accurate diagnosis potentially in real-time.
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.