ArticleOncotarget2016
A scoring system based on artificial neural network for predicting 10-year survival in stage II A colon cancer patients after radical surgery.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Pooled it
- Pim-3 as a potential predictor of chemoradiotherapy resistance in locally advanced rectal cancer patients.Scientific reports · 2017Trial
- Review
- Epigenetic and Tumor Microenvironment for Prognosis of Patients with Gastric Cancer.Biomolecules · 2023Article
- Preoperative Immunocite-Derived Ratios Predict Surgical Complications Better when Artificial Neural Networks Are Used for Analysis-A Pilot Comparative Study.Journal of personalized medicine · 2023Article
- Artificial Intelligence in Endoscopic Ultrasound for Pancreatic Cancer: Where Are We Now and What Does the Future Entail?Journal of clinical medicine · 2022Review
- Machine learning in gastrointestinal surgery.Surgery today · 2022Review
- Stage IV colon cancer patients without DENND2D expression benefit more from neoadjuvant chemotherapy.Cell death & disease · 2022Article
- External Validation of the Long Short-Term Memory Artificial Neural Network-Based SCaP Survival Calculator for Prediction of Prostate Cancer Survival.Cancer research and treatment · 2021Article
- Long short-term memory artificial neural network model for prediction of prostate cancer survival outcomes according to initial treatment strategy: development of an online decision-making support system.World journal of urology · 2020Article
- Development and validation of an artificial neural network prognostic model after gastrectomy for gastric carcinoma: An international multicenter cohort study.Cancer medicine · 2020Article
- Application of artificial intelligence to the diagnosis and therapy of colorectal cancer.American journal of cancer research · 2020Review
- Establishment of multiple diagnosis models for colorectal cancer with artificial neural networks.Oncology letters · 2019Article
- Artificial Neural Network Individualised Prediction of Time to Colorectal Cancer Surgery.Gastroenterology research and practice · 2019Article
- Article
- Expression of a novel CNPY2 isoform in colorectal cancer and its association with oncologic prognosis.Aging · 2017Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nearly 20% patients with stage II A colon cancer will develop recurrent disease post-operatively. The present study aims to develop a scoring system based on Artificial Neural Network (ANN) model for predicting 10-year survival outcome. The clinical and molecular data of 117 stage II A colon cancer patients from Sun Yat-sen University Cancer Center were used for training set and test set; poor pathological grading (score 49), reduced expression of TGFBR2 (score 33), over-expression of TGF-β (score 45), MAPK (score 32), pin1 (score 100), β-catenin in tumor tissue (score 50) and reduced expression of TGF-β in normal mucosa (score 22) were selected as the prognostic risk predictors. According to the developed scoring system, the patients were divided into 3 subgroups, which were supposed with higher, moderate and lower risk levels. As a result, for the 3 subgroups, the 10-year overall survival (OS) rates were 16.7%, 62.9% and 100% (P < 0.001); and the 10-year disease free survival (DFS) rates were 16.7%, 61.8% and 98.8% (P < 0.001) respectively. It showed that this scoring system for stage II A colon cancer could help to predict long-term survival and screen out high-risk individuals for more vigorous treatment.
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Registered trials
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