ArticleTheranostics2020
Prediction of clinically relevant Pancreatico-enteric Anastomotic Fistulas after Pancreatoduodenectomy using deep learning of Preoperative Computed Tomography.
Article in Theranostics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.
- Postoperative pancreatic fistula: a bibliometric analysis of research trends and a meta-analysis on the association with intra pancreatic fat deposition.Scientific reports · 2025Pooled it
- Artificial Intelligence in Pancreatic Imaging: A Systematic Review.United European gastroenterology journal · 2025Pooled it
- Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?Annals of gastroenterological surgery · 2026Review
- Article
- Advancements in Radiomics-Based AI for Pancreatic Ductal Adenocarcinoma.Bioengineering (Basel, Switzerland) · 2025Review
- Risk stratification of postoperative pancreatic fistula and other complications following pancreatoduodenectomy. How far are we? A scoping review.Langenbeck's archives of surgery · 2025Article
- Pancreatic Ductal Adenocarcinoma (PDAC): A Review of Recent Advancements Enabled by Artificial Intelligence.Cancers · 2024Review
- Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives.World journal of gastroenterology · 2024Review
- Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula.Scientific reports · 2024Article
- 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
- Machine learning models in clinical practice for the prediction of postoperative complications after major abdominal surgery.Surgery today · 2023Article
- Article
- An Unsupervised Learning-Based Regional Deformable Model for Automated Multi-Organ Contour Propagation.Journal of digital imaging · 2023Article
- Review
- Application of artificial intelligence to pancreatic adenocarcinoma.Frontiers in oncology · 2022Review
- Research trends of artificial intelligence in pancreatic cancer: a bibliometric analysis.Frontiers in oncology · 2022Article
- Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma.World journal of gastroenterology · 2021Review
- Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer.JMIR medical informatics · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
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.