ArticleBMC medical imaging2024
A deep learning-powered diagnostic model for acute pancreatitis.
Article in BMC medical imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- APEX-NET: automated pancreatic evaluation network using early non-contrast CT.European radiology · 2026Article
- Deep learning-based detection of acute pancreatitis on abdominal contrast-enhanced CT.European radiology experimental · 2026Article
- Machine learning model for early prediction of acute respiratory failure in acute pancreatitis: Multicenter validation.iScience · 2026Article
- Management and Prediction of Acute Pancreatitis Severity Using AI: A Surgical Perspective.Diagnostics (Basel, Switzerland) · 2026Review
- A Vision Transformer-Based Deep Learning Framework for Patient-Level Classification of Acute Pancreatitis and Normal Pancreas Using Computed Tomography.Diagnostics (Basel, Switzerland) · 2026Article
- Insights into Acute Pancreatitis: Pathogenesis, Diagnosis, and Management.Journal of clinical medicine · 2026Review
- Radiomics-Driven Machine Learning Models for Diagnosis of Pancreatic Adenocarcinoma.Iranian journal of medical sciences · 2026Article
- Deep learning-based multiclass classification for the diagnosis of hand arthritis on digital radiography: a multicenter study.Frontiers in medicine · 2026Article
- Demystifying anti-inflammatory therapeutic strategies against pancreatitis and concomitant diseases: a 2025 perspective.Theranostics · 2026Review
- Ultrasound and SWE-based transfer learning for predicting fibrotic NASH.Scientific reports · 2025Article
- Epidemiology, etiopathogenesis, immune response, diagnosis, and complications of acute pancreatitis: current insights.Annals of medicine · 2025Review
- Applications of artificial intelligence in abdominal imaging.Abdominal radiology (New York) · 2025Review
- AI and Machine Learning for Precision Medicine in Acute Pancreatitis: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Deep learning-assisted diagnosis of acute mesenteric ischemia based on CT angiography images.Frontiers in medicine · 2025Article
- Feasibility and Effectiveness of a Low-Code AI Platform for Developing a Neonatal Multimodal Pain Classification Model.Journal of multidisciplinary healthcare · 2025Article
- Relationship between pancreatic morphological changes and diabetes in autoimmune pancreatitis: Multimodal medical imaging assessment has important potential.World journal of radiology · 2024Article
- Radiograph-based rheumatoid arthritis diagnosis via convolutional neural network.BMC medical imaging · 2024Article
- Assessment of body composition and prediction of infectious pancreatic necrosis via non-contrast CT radiomics and deep learning.Frontiers in microbiology · 2024Article
- Mapping artificial intelligence models in emergency medicine: A scoping review on artificial intelligence performance in emergency care and education.Turkish journal of emergency medicineReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundAcute pancreatitis is one of the most common diseases requiring emergency surgery. Rapid and accurate recognition of acute pancreatitis can help improve clinical outcomes. This study aimed to develop a deep learning-powered diagnostic model for acute pancreatitis. MATERIALS AND
methodsIn this investigation, we enrolled a cohort of 190 patients with acute pancreatitis who were admitted to Sichuan Provincial People's Hospital between January 2020 and December 2021. Abdominal computed tomography (CT) scans were obtained from both patients with acute pancreatitis and healthy individuals. Our model was constructed using two modules: (1) the acute pancreatitis classifier module; (2) the pancreatitis lesion segmentation module. Each model's performance was assessed based on precision, recall rate, F1-score, Area Under the Curve (AUC), loss rate, frequency-weighted accuracy (fwavacc), and Mean Intersection over Union (MIOU).
resultsUpon admission, significant variations were observed between patients with mild and severe acute pancreatitis in inflammatory indexes, liver, and kidney function indicators, as well as coagulation parameters. The acute pancreatitis classifier module exhibited commendable diagnostic efficacy, showing an impressive AUC of 0.993 (95%CI: 0.978-0.999) in the test set (comprising healthy examination patients vs. those with acute pancreatitis, P < 0.001) and an AUC of 0.850 (95%CI: 0.790-0.898) in the external validation set (healthy examination patients vs. patients with acute pancreatitis, P < 0.001). Furthermore, the acute pancreatitis lesion segmentation module demonstrated exceptional performance in the validation set. For pancreas segmentation, peripancreatic inflammatory exudation, peripancreatic effusion, and peripancreatic abscess necrosis, the MIOU values were 86.02 (84.52, 87.20), 61.81 (56.25, 64.83), 57.73 (49.90, 68.23), and 66.36 (55.08, 72.12), respectively. These findings underscore the robustness and reliability of the developed models in accurately characterizing and assessing acute pancreatitis.
conclusionThe diagnostic model for acute pancreatitis, driven by deep learning, exhibits excellent efficacy in accurately evaluating the severity of the condition.
trial registrationThis is a retrospective study.
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.