ReviewCureus2024
Advancements in Pancreatic Cancer Detection: Integrating Biomarkers, Imaging Technologies, and Machine Learning for Early Diagnosis.
Review in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Dose-response relationship of cadmium and pancreatic cancer risk: a meta-analysis.Occupational and environmental medicine · 2025Pooled it
- Artificial Intelligence in Pancreatic Imaging: A Systematic Review.United European gastroenterology journal · 2025Pooled it
- 3D Modelling for Preoperative Planning, Intraoperative Navigation, and Training in Pancreatic Surgery: A Systematic Review.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026Review
- Detection and Classification of Pancreatic Cancer Nodules on CT Images using U-Net and Ensemble Models.Current medical imaging · 2026Article
- Optimized federated learning framework with RegNetZ and Swin-Transformer for multimodal pancreatic cancer detection1.Scientific reports · 2025Article
- Updates in the diagnosis and management of ductal adenocarcinoma of the pancreas.World journal of clinical oncology · 2025Review
- Artificial intelligence in pancreatic cancer histopathology and diagnostics - implications for clinical decisions and biomarker discovery?Cell division · 2025Review
- Artificial intelligence in gastrointestinal cancers: Diagnostic, prognostic, and surgical strategies.Cancer letters · 2025Review
- Artificial Intelligence in Pancreatic Image Analysis: A Review.Sensors (Basel, Switzerland) · 2024Review
- Technology and Future of Multi-Cancer Early Detection.Life (Basel, Switzerland) · 2024Review
- A single-cell perspective on immunotherapy for pancreatic cancer: from microenvironment analysis to therapeutic strategy innovation.Frontiers in immunology · 2024Review
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
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has come to play a pivotal role in revolutionizing medical practices, particularly in the field of pancreatic cancer detection and management. As a leading cause of cancer-related deaths, pancreatic cancer warrants innovative approaches due to its typically advanced stage at diagnosis and dismal survival rates. Present detection methods, constrained by limitations in accuracy and efficiency, underscore the necessity for novel solutions. AI-driven methodologies present promising avenues for enhancing early detection and prognosis forecasting. Through the analysis of imaging data, biomarker profiles, and clinical information, AI algorithms excel in discerning subtle abnormalities indicative of pancreatic cancer with remarkable precision. Moreover, machine learning (ML) algorithms facilitate the amalgamation of diverse data sources to optimize patient care. However, despite its huge potential, the implementation of AI in pancreatic cancer detection faces various challenges. Issues such as the scarcity of comprehensive datasets, biases in algorithm development, and concerns regarding data privacy and security necessitate thorough scrutiny. While AI offers immense promise in transforming pancreatic cancer detection and management, ongoing research and collaborative efforts are indispensable in overcoming technical hurdles and ethical dilemmas. This review delves into the evolution of AI, its application in pancreatic cancer detection, and the challenges and ethical considerations inherent in its integration.
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.