ReviewWorld journal of gastroenterology2021
Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma.
Review in World journal of gastroenterology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.
- Global research trends and hotspots in prognostic prediction models for pancreatic cancer: a bibliometric analysis.Frontiers in oncology · 2025Pooled it
- Mapping the global landscape of artificial intelligence in pancreatic cancer research: A bibliometric and visualization analysis.Medicine · 2026Article
- Deep Learning Framework for Early Detection of Pancreatic Cancer Using Multi-modal Medical Imaging Analysis.Journal of imaging informatics in medicine · 2026Article
- Advancements in Radiomics-Based AI for Pancreatic Ductal Adenocarcinoma.Bioengineering (Basel, Switzerland) · 2025Review
- Exploration of the current status and trends of pancreatic cancer immune cells in the past 30 years: a bibliometric analysis.Discover oncology · 2025Article
- The role of artificial intelligence in pancreatic surgery: Current and future perspectives.Annals of hepato-biliary-pancreatic surgery · 2025Article
- Data privacy-aware machine learning approach in pancreatic cancer diagnosis.BMC medical informatics and decision making · 2024Article
- Robust and consistent biomarker candidates identification by a machine learning approach applied to pancreatic ductal adenocarcinoma metastasis.BMC medical informatics and decision making · 2024Article
- Pancreatic Ductal Adenocarcinoma (PDAC): A Review of Recent Advancements Enabled by Artificial Intelligence.Cancers · 2024Review
- Network dynamics and therapeutic aspects of mRNA and protein markers with the recurrence sites of pancreatic cancer.Heliyon · 2024Article
- A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images.Diagnostics (Basel, Switzerland) · 2024Review
- Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis.World journal of gastroenterology · 2023Review
- Review
- Review
- Pancreatic cancer, radiomics and artificial intelligence.The British journal of radiology · 2022Review
- Early diagnosis of pancreatic cancer: What strategies to avoid a foretold catastrophe.World journal of gastroenterology · 2022Review
- Research trends of artificial intelligence in pancreatic cancer: a bibliometric analysis.Frontiers in oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal type of cancer. The 5-year survival rate for patients with early-stage diagnosis can be as high as 20%, suggesting that early diagnosis plays a pivotal role in the prognostic improvement of PDAC cases. In the medical field, the broad availability of biomedical data has led to the advent of the "big data" era. To overcome this deadly disease, how to fully exploit big data is a new challenge in the era of precision medicine. Artificial intelligence (AI) is the ability of a machine to learn and display intelligence to solve problems. AI can help to transform big data into clinically actionable insights more efficiently, reduce inevitable errors to improve diagnostic accuracy, and make real-time predictions. AI-based omics analyses will become the next alterative approach to overcome this poor-prognostic disease by discovering biomarkers for early detection, providing molecular/genomic subtyping, offering treatment guidance, and predicting recurrence and survival. Advances in AI may therefore improve PDAC survival outcomes in the near future. The present review mainly focuses on recent advances of AI in PDAC for clinicians. We believe that breakthroughs will soon emerge to fight this deadly disease using AI-navigated precision medicine.
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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.