ArticleGastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association2024
Multitask machine learning-based tumor-associated collagen signatures predict peritoneal recurrence and disease-free survival in gastric cancer.
Article in Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Clinical significance of intraoperative dissection time and machine learning-based prediction in laparoscopic distal gastrectomy for gastric cancer.Surgical endoscopy · 2026Article
- Research progress of machine learning applications in gastric cancer diagnosis and therapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- From Label-Free Multiphoton Imaging to Pathological Reports: A Vision-Language Breast Cancer Margin Pathological Diagnosis System.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Interpretable AI-driven prediction of early postoperative recurrence in locally advanced rectal cancer using the Systemic Inflammatory-Nutritional Index (SINTI): A multi-center study and clinical web tool.International journal of colorectal disease · 2026Article
- Development and temporal validation of a machine learning-based model to predict postoperative recurrence and guide adjuvant radiotherapy in patients with soft tissue sarcoma: a retrospective cohort study.American journal of cancer research · 2026Article
- A multi-task learning model for evaluating non-tumor gastric diseases indicators in whole slide images.Scientific reports · 2025Article
- Multimodal artificial intelligence technology in the precision diagnosis and treatment of gastroenterology and hepatology: Innovative applications and challenges.World journal of gastroenterology · 2025Review
- The Duality of Collagens in Metastases of Solid Tumors.International journal of molecular sciences · 2025Review
- Extracellular matrix dynamics in tumor immunoregulation: from tumor microenvironment to immunotherapy.Journal of hematology & oncology · 2025Review
- Concurrent prediction of in-hospital mortality and length of stay using single-task, multiclass and multitask machine learning.BMJ digital health & AI · 2025Article
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Authors and funding
14 authors.
Funding
Abstract
backgroundAccurate prediction of peritoneal recurrence for gastric cancer (GC) is crucial in clinic. The collagen alterations in tumor microenvironment affect the migration and treatment response of cancer cells. Herein, we proposed multitask machine learning-based tumor-associated collagen signatures (TACS), which are composed of quantitative collagen features derived from multiphoton imaging, to simultaneously predict peritoneal recurrence (TACS
methodsAmong 713 consecutive patients, with 275 in training cohort, 222 patients in internal validation cohort, and 216 patients in external validation cohort, we developed and validated a multitask machine learning model for simultaneously predicting peritoneal recurrence (TACS
resultsThe TACS
conclusionsThe multitask machine learning model allows accurate prediction of peritoneal recurrence and survival for GC and could distinguish patients who might benefit from adjuvant chemotherapy.
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