AIMC Topic: Esophageal Neoplasms
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Adaptive contrast weighted learning for multi-stage multi-treatment decision-making.
Biometrics
May 23, 2016
Dynamic treatment regimes (DTRs) are sequential decision rules that focus simultaneously on treatment individualization and adaptation over time. To directly identify the optimal DTR in a multi-stage multi-treatment setting, we propose a dynamic stat...
Early Experience of Robot-Assisted Esophagectomy With Circular End-to-End Stapled Anastomosis.
The Annals of thoracic surgery
May 4, 2016
BACKGROUND: Surgical resection is a critical element in the treatment of esophageal cancer. Esophagectomy is technically challenging and is associated with high morbidity and mortality rates. Efforts to reduce these rates have spurred the adoption of...
Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks.
PloS one
Sep 10, 2015
Imaging of cancer with 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) has become a standard component of diagnosis and staging in oncology, and is becoming more important as a quantitative monitor of individual response to therapy....
Oncologic Long-Term Results of Robot-Assisted Minimally Invasive Thoraco-Laparoscopic Esophagectomy with Two-Field Lymphadenectomy for Esophageal Cancer.
Annals of surgical oncology
May 29, 2015
BACKGROUND: Open transthoracic esophagectomy is the worldwide gold standard in the treatment of resectable esophageal cancer. Robot-assisted minimally invasive thoraco-laparoscopic esophagectomy (RAMIE) for esophageal cancer may be associated with re...
Integration of machine learning in biomarker discovery for esophageal squamous cell carcinoma: Applications and future directions.
Pathology, research and practice
Aug 1, 2025
PURPOSE: Recent advancements in sequencing technologies and bioinformatics algorithms have facilitated significant breakthroughs in both fundamental and clinical tumor research. Nevertheless, the processing and utilization of large-scale data continu...
Artificial intelligence-assisted endoscopic ultrasound diagnosis of esophageal subepithelial lesions.
Surgical endoscopy
Jun 1, 2025
BACKGROUND: Endoscopic ultrasound (EUS) is one of the most accurate methods for determining the originating layer of subepithelial lesions (SELs). However, the accuracy is greatly influenced by the expertise and proficiency of the endoscopist. In thi...
Automated machine learning model for predicting anastomotic strictures after esophageal cancer surgery: a retrospective cohort study.
Surgical endoscopy
Jun 1, 2025
BACKGROUND: Anastomotic strictures (AS) frequently occurs in patients following esophageal cancer surgery, significantly affecting their long-term quality of life. This study aims to develop a machine learning model to predict high-risk AS, enabling ...
Characterization of subepithelial tumors of upper gastrointestinal tract by endoscopic ultrasound.
World journal of gastroenterology
May 21, 2025
In this article we comment on the paper by Xu describing retrospective data on endoscopic treatment outcome of esophageal gastrointestinal stromal tumors (GISTs). Esophageal GIST is a rare type of mesenchymal tumor. GISTs originate from the intersti...
Application of deep learning models in the pathological classification and staging of esophageal cancer: A focus on Wave-Vision Transformer.
World journal of gastroenterology
May 21, 2025
BACKGROUND: Esophageal cancer is the sixth most common cancer worldwide, with a high mortality rate. Early prognosis of esophageal abnormalities can improve patient survival rates. The progression of esophageal cancer follows a sequence from esophagi...
Automating Performance Status Annotation in Oncology Using Llama-3.
Studies in health technology and informatics
May 15, 2025
This work explores the automated extraction of medical information from Dutch clinical notes using Llama-3 and a limited amount of annotations. We compared zero-, one- and few-shot learning for the extraction of performance status of patients with pa...
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