ArticleArtificial intelligence surgery2023
Potential of artificial intelligence in the risk stratification for and early detection of pancreatic cancer.
Article in Artificial intelligence surgery, 2023. 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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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.
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Who cites it
10 citing papers in PubMed.
- Artificial Intelligence in Pancreatobiliary Endoscopy: Current Advances, Opportunities, and Challenges.Journal of clinical medicine · 2025Review
- Unveiling genetic susceptibility in esophageal squamous cell carcinoma and revolutionizing pancreatic cancer diagnosis through imaging.World journal of gastrointestinal oncology · 2025Article
- Review
- Development and validation of a nomogram for predicting postoperative intraluminal hemorrhage in patients undergoing laparoscopic pancreaticoduodenectomy.Frontiers in surgery · 2025Article
- The Prognostic Significance of the CALLY Index in Ampullary Carcinoma: An Inflammation-Nutrition Retrospective Analysis.Journal of inflammation research · 2025Article
- Early detection of pancreatic cancer: Study design and analytical considerations in biomarker discovery and early phase validation studies.Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2024Review
- Understanding the Conundrum of Pancreatic Cancer in the Omics Sciences Era.International journal of molecular sciences · 2024Review
- Pancreatic Ductal Adenocarcinoma: Update of CT-Based Radiomics Applications in the Pre-Surgical Prediction of the Risk of Post-Operative Fistula, Resectability Status and Prognosis.Journal of clinical medicine · 2023Review
- Review
- Risk Assessment and Radiomics Analysis in Magnetic Resonance Imaging of Pancreatic Intraductal Papillary Mucinous Neoplasms (IPMN).Cancer control : journal of the Moffitt Cancer CenterReview
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the third most lethal cancer in the United States, with a 5-year life expectancy of 11%. Most symptoms manifest at an advanced stage of the disease when surgery is no longer appropriate. The dire prognosis of PDAC warrants new strategies to improve the outcomes of patients, and early detection has garnered significant attention. However, early detection of PDAC is most often incidental, emphasizing the importance of developing new early detection screening strategies. Due to the low incidence of the disease in the general population, much of the focus for screening has turned to individuals at high risk of PDAC. This enriches the screening population and balances the risks associated with pancreas interventions. The cancers that are found in these high-risk individuals by MRI and/or EUS screening show favorable 73% 5-year overall survival. Even with the emphasis on screening in enriched high-risk populations, only a minority of incident cancers are detected this way. One strategy to improve early detection outcomes is to integrate artificial intelligence (AI) into biomarker discovery and risk models. This expert review summarizes recent publications that have developed AI algorithms for the applications of risk stratification of PDAC using radiomics and electronic health records. Furthermore, this review illustrates the current uses of radiomics and biomarkers in AI for early detection of PDAC. Finally, various challenges and potential solutions are highlighted regarding the use of AI in medicine for early detection purposes.
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Registered trials
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