AIMC Topic: Pancreatic Neoplasms
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Enhancing noninvasive pancreatic cystic neoplasm diagnosis with multimodal machine learning.
Scientific reports
May 12, 2025
Pancreatic cystic neoplasms (PCNs) are a complex group of lesions with a spectrum of malignancy. Accurate differentiation of PCN types is crucial for patient management, as misdiagnosis can result in unnecessary surgeries or treatment delays, affecti...
A Novel Deep Learning-based Pathomics Score for Prognostic Stratification in Pancreatic Ductal Adenocarcinoma.
Pancreas
May 1, 2025
BACKGROUND AND OBJECTIVES: Accurate survival prediction for pancreatic ductal adenocarcinoma (PDAC) is crucial for personalized treatment strategies. This study aims to construct a novel pathomics indicator using hematoxylin and eosin-stained whole s...
Mitigation of outcome conflation in predicting patient outcomes using electronic health records.
Journal of the American Medical Informatics Association : JAMIA
May 1, 2025
OBJECTIVES: Artificial intelligence (AI) models utilizing electronic health record data for disease prediction can enhance risk stratification but may lack specificity, which is crucial for reducing the economic and psychological burdens associated w...
RRM-TransUNet: Deep-Learning Driven Interactive Model for Precise Pancreas Segmentation in CT Images.
The international journal of medical robotics + computer assisted surgery : MRCAS
Apr 1, 2025
BACKGROUND: Pancreatic diseases such as cancer and pancreatitis pose significant health risks. Early detection requires precise segmentation results. Fully automatic segmentation algorithms cannot integrate clinical expertise and correct output error...
Developing a Predictive Model for Metastatic Potential in Pancreatic Neuroendocrine Tumor.
The Journal of clinical endocrinology and metabolism
Dec 18, 2024
CONTEXT: Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive.
Predicting Pancreatic Cancer in New-Onset Diabetes Cohort Using a Novel Model With Integrated Clinical and Genetic Indicators: A Large-Scale Prospective Cohort Study.
Cancer medicine
Nov 1, 2024
INTRODUCTION: Individuals who develop new-onset diabetes have been identified as a high-risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this spec...
Deep-Transfer-Learning-Based Natural Language Processing of Serial Free-Text Computed Tomography Reports for Predicting Survival of Patients With Pancreatic Cancer.
JCO clinical cancer informatics
Aug 1, 2024
PURPOSE: To explore the predictive potential of serial computed tomography (CT) radiology reports for pancreatic cancer survival using natural language processing (NLP).
Artificial intelligence-based tools with automated segmentation and measurement on CT images to assist accurate and fast diagnosis in acute pancreatitis.
The British journal of radiology
Jun 18, 2024
OBJECTIVES: To develop an artificial intelligence (AI) tool with automated pancreas segmentation and measurement of pancreatic morphological information on CT images to assist improved and faster diagnosis in acute pancreatitis.
Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.
Cancer immunology research
May 2, 2024
Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multipl...
[Applications of Artificial Intelligence in Pancreatic Cystic Lesion Imaging].
Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae
Apr 1, 2024
As the detection rate of pancreatic cystic lesions(PCL)increases,artificial intelligence(AI)has made breakthroughs in the imaging workflow of PCL,including image post-processing,lesion detection,segmentation,diagnosis and differential diagnosis.AI-ba...
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