ArticleJournal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract2017
An Evaluation of Artificial Neural Networks in Predicting Pancreatic Cancer Survival.
Article in Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03632850 (Shared Decision-making), which is not on this map. Cited by 16 papers, 2 of them syntheses 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.
Shared Decision-making: Investigating the Potential of an Interactive, Web-Based, Information Tool for People With Advanced Pancreatic Cancer
Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Irreversible Electroporation in Patients with Pancreatic Cancer: How Important Is the New Weapon?BioMed research international · 2018Pooled it
- Establishment of prediction model for mortality risk of pancreatic cancer: a retrospective study.BMC medical informatics and decision making · 2024Article
- A Quest for Survival: A Review of the Early Biomarkers of Pancreatic Cancer and the Most Effective Approaches at Present.Biomolecules · 2024Review
- Advances in biomarkers and techniques for pancreatic cancer diagnosis.Cancer cell international · 2022Review
- A Machine Learning Approach to Screen for Otitis Media Using Digital Otoscope Images Labelled by an Expert Panel.Diagnostics (Basel, Switzerland) · 2022Article
- Artificial intelligence in pancreatic cancer.Theranostics · 2022Review
- Application of artificial intelligence to pancreatic adenocarcinoma.Frontiers in oncology · 2022Review
- Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma.World journal of gastroenterology · 2021Review
- Artificial intelligence in gastroenterology: A state-of-the-art review.World journal of gastroenterology · 2021Review
- A method for utilizing automated machine learning for histopathological classification of testis based on Johnsen scores.Scientific reports · 2021Article
- Artificial intelligence for early detection of pancreatic adenocarcinoma: The future is promising.World journal of gastroenterology · 2021Review
- Artificial intelligence for the management of pancreatic diseases.Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society · 2021Review
- Establishment and application of an artificial intelligence diagnosis system for pancreatic cancer with a faster region-based convolutional neural network.Chinese medical journal · 2019Article
- Building an Otoscopic screening prototype tool using deep learning.Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale · 2019Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aims to evaluate the development of an artificial neural network (ANN) method for predicting the survival likelihood of pancreatic adenocarcinoma patients. The ANN predictive model should produce results with a 90% sensitivity.
methodsA prospective examination of the records for 283 consecutive pancreatic adenocarcinoma patients is used to identify 219 records with complete data. These records are then used to create two unique samples which are then used to train and validate an ANN predictive model. Numerous network architectures are evaluated, following recommended ANN development protocols.
resultsSeveral backpropagation-trained ANNs were produced that satisfied the 90% sensitivity requirement. An ANN model with over a 91% sensitivity is selected because even though it did not have the highest sensitivity, it was able to achieve over 38% specificity.
conclusionsANN models can accurately predict the 7-month survival of pancreatic adenocarcinoma patients, both with and without resection, at a 91% sensitivity and 38% specificity. This implies that ANN models may be useful objective decision tools in complex treatment decisions. This information may be used by patients and surgeons in determining optimal treatment plans that minimize regret and improve the quality of life for these patients.
Indexed as
Identifiers
28776157What 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.