ArticleJournal of computer assisted tomography
Support Vector Machines Model of Computed Tomography for Assessing Lymph Node Metastasis in Esophageal Cancer with Neoadjuvant Chemotherapy.
Article in Journal of computer assisted tomography. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 3 syntheses or guidelines pooled it, 29 citations in OpenAlex.
- The Impact and Role of Artificial Intelligence (AI) in Healthcare: Systematic Review.Current topics in medicinal chemistry · 2025Pooled it
- Performance of radiomics-based artificial intelligence systems in the diagnosis and prediction of treatment response and survival in esophageal cancer: a systematic review and meta-analysis of diagnostic accuracy.Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus · 2023Pooled it
- Diagnostic Performance of Artificial Intelligence-Centred Systems in the Diagnosis and Postoperative Surveillance of Upper Gastrointestinal Malignancies Using Computed Tomography Imaging: A Systematic Review and Meta-Analysis of Diagnostic Accuracy.Annals of surgical oncology · 2022Pooled it
- Value of Computed Tomography Scan for Detecting Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma.Annals of surgical oncology · 2025Article
- Review
- ARMO: automated and reliable multi-objective model for lymph node metastasis prediction in head and neck cancer.Physics in medicine and biology · 2023Article
- Identification of Potential Diagnostic Genes of HIV-Infected Immunological Non-Responders on Bioinformatics Analysis.Journal of inflammation research · 2023Article
- Global research trends of artificial intelligence applied in esophageal carcinoma: A bibliometric analysis (2000-2022)Frontiers in oncology · 2022Article
- Detecting lymph node metastasis of esophageal cancer on dual-energy computed tomography.Acta radiologica (Stockholm, Sweden : 1987) · 2022Article
- Development and validation of a nomogram model for the prediction of 4L lymph node metastasis in thoracic esophageal squamous cell carcinoma.Frontiers in oncology · 2022Article
- Analysis of immune cell components and immune-related gene expression profiles in peripheral blood of patients with type 1 diabetes mellitus.Journal of translational medicine · 2021Article
- Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods.Frontiers in cardiovascular medicine · 2021Review
- Artificial intelligence performance in detecting tumor metastasis from medical radiology imaging: A systematic review and meta-analysis.EClinicalMedicine · 2021Article
- Artificial intelligence-assisted esophageal cancer management: Now and future.World journal of gastroenterology · 2020Review
- Increased Nucleus Accumbens Connectivity in Resting-State Patients With Drug-Naive, First-Episode Somatization Disorder.Frontiers in psychiatry · 2019Article
- Methotrexate remediates spinal cord injuryExperimental and therapeutic medicine · 2018Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of this study was to diagnose lymph node metastasis of esophageal cancer by support vector machines model based on computed tomography. MATERIALS AND
methodsA total of 131 esophageal cancer patients with preoperative chemotherapy and radical surgery were included. Various indicators (tumor thickness, tumor length, tumor CT value, total number of lymph nodes, and long axis and short axis sizes of largest lymph node) on CT images before and after neoadjuvant chemotherapy were recorded. A support vector machines model based on these CT indicators was built to predict lymph node metastasis.
resultsSupport vector machines model diagnosed lymph node metastasis better than preoperative short axis size of largest lymph node on CT. The area under the receiver operating characteristic curves were 0.887 and 0.705, respectively.
conclusionsThe support vector machine model of CT images can help diagnose lymph node metastasis in esophageal cancer with preoperative chemotherapy.
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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.