ArticleAnnals of surgical oncology2021
Integrating Machine Learning and Tumor Immune Signature to Predict Oncologic Outcomes in Resected Biliary Tract Cancer.
Article in Annals of surgical oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Predicting postoperative delayed awakening after flexible ureteroscopic lithotripsy based on radiomic features of body composition.Scientific reports · 2026Article
- Low gamma-butyrobetaine dioxygenase (BBOX1) expression as a prognostic biomarker in patients with clear cell renal cell carcinoma: a machine learning approach.The journal of pathology. Clinical research · 2023Article
- High PPFIA1 expression promotes cancer survival by suppressing CD8+ T cells in breast cancer: drug discovery and machine learning approach.Breast cancer (Tokyo, Japan) · 2023Article
- Machine learning in gastrointestinal surgery.Surgery today · 2022Review
- MiR-206 suppresses the deterioration of intrahepatic cholangiocarcinoma and promotes sensitivity to chemotherapy by inhibiting interactions with stromal CAFs.International journal of biological sciences · 2022Article
- A Clinical-Radiomic Model for Predicting Indocyanine Green Retention Rate at 15 Min in Patients With Hepatocellular Carcinoma.Frontiers in surgery · 2022Article
- A Study of the Recent Trends of Immunology: Key Challenges, Domains, Applications, Datasets, and Future Directions.Sensors (Basel, Switzerland) · 2021Review
- Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.Scientific reports · 2021Article
- High BMI1 Expression with Low CD8+ and CD4+ T Cell Activity Could Promote Breast Cancer Cell Survival: A Machine Learning Approach.Journal of personalized medicine · 2021Article
- High WHSC1L1 Expression Reduces Survival Rates in Operated Breast Cancer Patients with Decreased CD8+ T Cells: Machine Learning Approach.Journal of personalized medicine · 2021Article
- Applied machine learning in cancer research: A systematic review for patient diagnosis, classification and prognosis.Computational and structural biotechnology journal · 2021Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundImproved methods are needed to predict outcomes in biliary tract cancers (BTCs). We aimed to build an immune-related signature and establish holistic models using machine learning.
methodsSamples were from 305 BTC patients treated with curative-intent resection, divided into derivation and validation cohorts in a two-to-one ratio. Spatial resolution of T cell infiltration and PD-1/PD-L1 expression was assessed by immunohistochemistry. An immune signature was constructed using classification and regression tree. Machine learning was applied to develop prediction models for disease-specific survival (DSS) and recurrence-free survival (RFS).
resultsThe immune signature composed of CD3
conclusionsThe immune signature promises to stratify prognosis and allocate treatment in resected BTC. The clinical-immune GBM models accurately predict recurrence and death from BTC following surgery.
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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.