ReviewWorld journal of gastroenterology2023
Artificial intelligence as a noninvasive tool for pancreatic cancer prediction and diagnosis.
Review in World journal of gastroenterology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review and meta-analysis: diagnostic accuracy of exosomes in pancreatic cancer.World journal of surgical oncology · 2025Pooled it
- Deep Learning Framework for Early Detection of Pancreatic Cancer Using Multi-modal Medical Imaging Analysis.Journal of imaging informatics in medicine · 2026Article
- Decision support tools for pancreatic cancer detection: external validation in Australian primary care - a retrospective cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026Article
- Insights into artificial intelligence-based digital pathology in hepatobiliary and pancreatic cancer.Frontiers in oncology · 2026Review
- The development of a multimodal prediction model based on CT and MRI for the prognosis of pancreatic cancer.BMC gastroenterology · 2025Article
- PDAC: advances in tumour microenvironment, microbiome and AI.Nature reviews. Gastroenterology & hepatology · 2025Article
- Combining multimodal medical imaging and artificial intelligence for the early diagnosis of pancreatic cancer.Frontiers in medicine · 2025Article
- Pancreatic Adenocarcinoma: Imaging Modalities and the Role of Artificial Intelligence in Analyzing CT and MRI Images.Diagnostics (Basel, Switzerland) · 2024Review
- Deep Learning Applications in Pancreatic Cancer.Cancers · 2024Review
- 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
- Epidemiology of pancreatic cancer: New version, new vision.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2023Article
- Risk Assessment and Radiomics Analysis in Magnetic Resonance Imaging of Pancreatic Intraductal Papillary Mucinous Neoplasms (IPMN).Cancer control : journal of the Moffitt Cancer CenterReview
- Predicting early gastric cancer risk using machine learning: A population-based retrospective study.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic cancer (PC) has a low incidence rate but a high mortality, with patients often in the advanced stage of the disease at the time of the first diagnosis. If detected, early neoplastic lesions are ideal for surgery, offering the best prognosis. Preneoplastic lesions of the pancreas include pancreatic intraepithelial neoplasia and mucinous cystic neoplasms, with intraductal papillary mucinous neoplasms being the most commonly diagnosed. Our study focused on predicting PC by identifying early signs using noninvasive techniques and artificial intelligence (AI). A systematic English literature search was conducted on the PubMed electronic database and other sources. We obtained a total of 97 studies on the subject of pancreatic neoplasms. The final number of articles included in our study was 44, 34 of which focused on the use of AI algorithms in the early diagnosis and prediction of pancreatic lesions. AI algorithms can facilitate diagnosis by analyzing massive amounts of data in a short period of time. Correlations can be made through AI algorithms by expanding image and electronic medical records databases, which can later be used as part of a screening program for the general population. AI-based screening models should involve a combination of biomarkers and medical and imaging data from different sources. This requires large numbers of resources, collaboration between medical practitioners, and investment in medical infrastructures.
Indexed as
Identifiers
What Socratic 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 Socratic graph.