AIMC Topic: Esophageal Neoplasms
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ChatEndoscopist: A Domain-Specific Chatbot with Images for Gastrointestinal Diseases.
Studies in health technology and informatics
May 15, 2025
This study aims to enhance domain-specific medical knowledge within large language models (LLMs) by developing a chatbot, chatEndoscopist, a specialized model for oesophageal cancer. In particular, the chatbot incorporates related images to further e...
Clinical Implications of The Cancer Genome Atlas Molecular Classification System in Esophagogastric Cancer.
Clinical cancer research : an official journal of the American Association for Cancer Research
May 15, 2025
PURPOSE: The Cancer Genome Atlas (TCGA) project defined four distinct molecular subtypes of esophagogastric adenocarcinoma: microsatellite instable (MSI), Epstein-Barr virus (EBV)-associated, genomically stable (GS), and chromosomally instable (CIN)....
A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights.
BMC gastroenterology
May 10, 2025
OBJECTIVE: This study aims to create a reliable framework for grading esophageal cancer. The framework combines feature extraction, deep learning with attention mechanisms, and radiomics to ensure accuracy, interpretability, and practical use in tumo...
Rapid pathologic grading-based diagnosis of esophageal squamous cell carcinoma Raman spectroscopy and a deep learning algorithm.
World journal of gastroenterology
Apr 14, 2025
BACKGROUND: Esophageal squamous cell carcinoma is a major histological subtype of esophageal cancer. Many molecular genetic changes are associated with its occurrence. Raman spectroscopy has become a new method for the early diagnosis of tumors becau...
Artificial intelligence-aided optical biopsy improves the diagnosis of esophageal squamous neoplasm.
World journal of gastroenterology
Apr 7, 2025
BACKGROUND: Early detection of esophageal squamous neoplasms (ESN) is essential for improving patient prognosis. Optical diagnosis of ESN remains challenging. Probe-based confocal laser endomicroscopy (pCLE) enables accurate histological observation...
Machine Learning-Based Glycolipid Metabolism Gene Signature Predicts Prognosis and Immune Landscape in Oesophageal Squamous Cell Carcinoma.
Journal of cellular and molecular medicine
Mar 1, 2025
Using machine learning approaches, we developed and validated a novel prognostic model for oesophageal squamous cell carcinoma (ESCC) based on glycolipid metabolism-related genes. Through integrated analysis of TCGA and GEO datasets, we established a...
Integrated machine learning developed a prognosis-related gene signature to predict prognosis in oesophageal squamous cell carcinoma.
Journal of cellular and molecular medicine
Nov 1, 2024
The mortality rate of oesophageal squamous cell carcinoma (ESCC) remains high, and conventional TNM systems cannot accurately predict its prognosis, thus necessitating a predictive model. In this study, a 17-gene prognosis-related gene signature (PRS...
Artificial intelligence enhances the management of esophageal squamous cell carcinoma in the precision oncology era.
World journal of gastroenterology
Oct 21, 2024
Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer with a poor prognosis. Early diagnosis and prognosis assessment are crucial for improving the survival rate of ESCC patients. With the advancement of ...
Automatic segmentation of esophageal cancer, metastatic lymph nodes and their adjacent structures in CTA images based on the UperNet Swin network.
Cancer medicine
Sep 1, 2024
OBJECTIVE: To create a deep-learning automatic segmentation model for esophageal cancer (EC), metastatic lymph nodes (MLNs) and their adjacent structures using the UperNet Swin network and computed tomography angiography (CTA) images and to improve t...
Using Machine Learning and miRNA for the Diagnosis of Esophageal Cancer.
The journal of applied laboratory medicine
Jul 1, 2024
BACKGROUND: Esophageal cancer (EC) remains a global health challenge, often diagnosed at advanced stages, leading to high mortality rates. Current diagnostic tools for EC are limited in their efficacy. This study aims to harness the potential of micr...
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