ArticleArchives of medical science : AMS2023
Deep learning survival model for colorectal cancer patients (DeepCRC) with Asian clinical data compared with different theories.
Article in Archives of medical science : AMS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Artificial Intelligence Models for Time-to-Event Outcome Applied in Cardiovascular Disease Risk Prediction.Journal of medical systems · 2024Pooled it
- Integrating Blood-Based Immune-Inflammation Biomarkers into Artificial Intelligence-Driven Prognostic Models in Oncology.International journal of molecular sciences · 2026Review
- Deep multimodal fusion of patho-radiomic and clinical data for enhanced survival prediction for colorectal cancer patients.NPJ digital medicine · 2025Article
- A Novel Ensemble Framework for Comprehensive Early-Stage Colorectal Cancer Diagnosis, Prognosis, and Treatment: Integration of Gastroenterology-Specific Transformer Language Models and Multiple Decision Trees.Journal of clinical medicine · 2025Article
- Unlocking the future: mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response.Translational cancer research · 2025Article
- Unlocking the future: Mitochondrial genes and neural networks in predicting ovarian cancer prognosis and immunotherapy response.World journal of clinical oncology · 2025Article
- Development of an individualized dementia risk prediction model using deep learning survival analysis incorporating genetic and environmental factors.Alzheimer's research & therapy · 2024Article
- Unveiling the secrets of gastrointestinal mucous adenocarcinoma survival after surgery with artificial intelligence: A population-based study.World journal of gastrointestinal oncology · 2024Article
- The development of a prediction model based on deep learning for prognosis prediction of gastrointestinal stromal tumor: a SEER-based study.Scientific reports · 2024Article
- Develop prediction model to help forecast advanced prostate cancer patients' prognosis after surgery using neural network.Frontiers in endocrinology · 2024Article
- Causal associations between liver traits and Colorectal cancer: a Mendelian randomization study.BMC medical genomics · 2023Article
- Preventive effects of 13 different drugs on colorectal cancer: a network meta-analysis.Archives of medical science : AMS · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Colorectal cancer (CRC) is the third most common cancer. Precise prediction of CRC patients' overall survival (OS) probability could offer advice on its treatment. Neural network (NN) is the first-class algorithm, but a consensus on which NN survival models are better has not been established yet. A predictive model on CRC using Asian data is also lacking. Methods: We conducted 8 NN survival models of CRC ( Results: DeepSurv performed best with a C-index value of 0.8300 in the training cohort and 0.7681 in the test cohort. Conclusions: The deep learning survival model for CRC patients (DeepCRC) could predict CRC's OS accurately.
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.