ArticleFrontiers in artificial intelligence2020
Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma.
Article in Frontiers in artificial intelligence, 2020. 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
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
11 citing papers in PubMed, 15 citations in OpenAlex.
- Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images.Scientific reports · 2021Trial
- A transfer learning-based hybrid deep- and machine-learning regression approach for predicting the postoperative pulmonary function.European radiology experimental · 2026Article
- Clinical Applications of Quantitative Imaging and Artificial Intelligence for Pancreatic Cance.Seminars in radiation oncology · 2025Review
- Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.Journal of medical systems · 2025Article
- Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer.World journal of radiology · 2023Article
- AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer.NPJ precision oncology · 2023Article
- Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview.World journal of gastroenterology · 2022Review
- Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis.Gastroenterology · 2022Article
- Pancreatic cancer, radiomics and artificial intelligence.The British journal of radiology · 2022Review
- Review
- Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma.Frontiers in artificial intelligence · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 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.