AIMC Topic: Adenocarcinoma
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Development and validation of CT-based fusion model for preoperative prediction of invasion and lymph node metastasis in adenocarcinoma of esophagogastric junction.
BMC medical imaging
Jul 1, 2025
PURPOSE: In the context of precision medicine, radiomics has become a key technology in solving medical problems. For adenocarcinoma of esophagogastric junction (AEG), developing a preoperative CT-based prediction model for AEG invasion and lymph nod...
A hybrid multi-instance learning-based identification of gastric adenocarcinoma differentiation on whole-slide images.
Biomedical engineering online
Jun 25, 2025
OBJECTIVE: To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining Transformer and graph attention networks for classifying gastric adenocarcinoma differentiation on whole-slide images (WSIs) without manual annotation...
[Incidental pulmonary nodules on CT imaging: what to do?].
Nederlands tijdschrift voor geneeskunde
Jun 23, 2025
Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage) lung cancers without any signs or symptoms. These incidental findings can be solid lesions or ground glass lesions that may be solitary or multiple. ...
Multi-omics identifies OSM-OSMR as a key receptor-ligand in the tumor environment of endometrial adenocarcinoma.
International immunopharmacology
May 31, 2025
Endometrial adenocarcinoma carries a bleak prognosis, and the molecular markers that evaluate the progression of endometrial adenocarcinoma to advanced stages remain uncertain. Cell-cell communication plays a crucial role in the tumor microenvironmen...
Oncostatin M
Humans
Oncostatin M Receptor beta Subunit
Prognosis
Multiomics
Gene Expression Profiling
Adenocarcinoma
Female
Gene Expression Regulation, Neoplastic
Mice, Nude
Transcriptome
Tumor Microenvironment
Cell Proliferation
Ligands
Animals
Cell Line, Tumor
Signal Transduction
Endometrial Neoplasms
Mice
Development and application of deep learning-based diagnostics for pathologic diagnosis of gastric endoscopic submucosal dissection specimens.
Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Apr 15, 2025
BACKGROUND: Accurate diagnosis of ESD specimens is crucial for managing early gastric cancer. Identifying tumor areas in serially sectioned ESD specimens requires experience and is time-consuming. This study aimed to develop and evaluate a deep learn...
Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single-center retrospective study in China.
Journal of applied clinical medical physics
Apr 11, 2025
PURPOSE: To assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC).
Automated classification of tertiary lymphoid structures in colorectal cancer using TLS-PAT artificial intelligence tool.
Scientific reports
Mar 21, 2025
Colorectal cancer (CRC) ranks as the third most common and second deadliest cancer worldwide. The immune system, particularly tertiary lymphoid structures (TLS), significantly influences CRC progression and prognosis. TLS maturation, especially in th...
Machine learning prediction of overall survival in prostate adenocarcinoma using ensemble techniques.
Computers in biology and medicine
Mar 12, 2025
Prostate adenocarcinoma (PAC) is a complex and common cancer in males and is one of the leading causes of cancer-related death globally. PAC is a multifaceted disease that encompasses different subtypes, including acinar and ductal adenocarcinoma, sm...
Self-supervised learning reveals clinically relevant histomorphological patterns for therapeutic strategies in colon cancer.
Nature communications
Mar 8, 2025
Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-eosin-stained whole slide images (WSIs). We train an SSL Barlow Twins encoder on 435 colon adenocarcinoma WSIs from The C...
Development and external validation of a machine learning-based model to predict postoperative recurrence in patients with duodenal adenocarcinoma: a multicenter, retrospective cohort study.
BMC medicine
Feb 21, 2025
BACKGROUND: Duodenal adenocarcinoma (DA) has a high recurrence rate, making the prediction of recurrence after surgery critically important.
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