AIMC Topic: Esophageal Neoplasms
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Deep Learning for Histopathological Assessment of Esophageal Adenocarcinoma Precursor Lesions.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jun 1, 2024
Histopathological assessment of esophageal biopsies is a key part in the management of patients with Barrett esophagus (BE) but prone to observer variability and reliable diagnostic methods are needed. Artificial intelligence (AI) is emerging as a po...
Personalized Composite Dosimetric Score-Based Machine Learning Model of Severe Radiation-Induced Lymphopenia Among Patients With Esophageal Cancer.
International journal of radiation oncology, biology, physics
May 24, 2024
PURPOSE: Radiation-induced lymphopenia (RIL) is common among patients undergoing radiation therapy (RT)' Severe RIL has been linked to adverse outcomes. The severity and risk of RIL can be predicted from baseline clinical characteristics and dosimetr...
Interpretable machine learning for predicting the response duration to Sintilimab plus chemotherapy in patients with advanced gastric or gastroesophageal junction cancer.
Frontiers in immunology
May 22, 2024
BACKGROUND: Sintilimab plus chemotherapy has proven effective as a combination immunotherapy for patients with advanced gastric and gastroesophageal junction adenocarcinoma (GC/GEJC). A multi-center study conducted in China revealed a median progress...
Raman spectroscopy for esophageal tumor diagnosis and delineation using machine learning and the portable Raman spectrometer.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
May 12, 2024
Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the curre...
Efficiency of endoscopic artificial intelligence in the diagnosis of early esophageal cancer.
Thoracic cancer
Apr 29, 2024
BACKGROUND: The accuracy of artificial intelligence (AI) and experts in diagnosing early esophageal cancer (EC) and its infiltration depth was summarized and analyzed, thus identifying the advantages of AI over traditional manual diagnosis, with a vi...
Deep learning assists detection of esophageal cancer and precursor lesions in a prospective, randomized controlled study.
Science translational medicine
Apr 17, 2024
Endoscopy is the primary modality for detecting asymptomatic esophageal squamous cell carcinoma (ESCC) and precancerous lesions. Improving detection rate remains challenging. We developed a system based on deep convolutional neural networks (CNNs) fo...
Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesions.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 16, 2024
Accurate segmentation of lesions is crucial for diagnosis and treatment of early esophageal cancer (EEC). However, neither traditional nor deep learning-based methods up to today can meet the clinical requirements, with the mean Dice score - the most...
HRU-Net: A high-resolution convolutional neural network for esophageal cancer radiotherapy target segmentation.
Computer methods and programs in biomedicine
Apr 14, 2024
BACKGROUND AND OBJECTIVE: The effective segmentation of esophageal squamous carcinoma lesions in CT scans is significant for auxiliary diagnosis and treatment. However, accurate lesion segmentation is still a challenging task due to the irregular for...
Long-term quality of life after hybrid robot-assisted and open Ivor Lewis esophagectomy for esophageal cancer in a single center: a comparative analysis.
Langenbeck's archives of surgery
Apr 11, 2024
PURPOSE: Due to improved survival of esophageal cancer patients, long-term quality of life (QoL) is increasingly gaining importance. The aim of this study is to compare QoL outcomes between open Ivor Lewis esophagectomy (Open-E) and a hybrid approach...
Deep-learning-based image super-resolution of an end-expandable optical fiber probe for application in esophageal cancer diagnostics.
Journal of biomedical optics
Apr 4, 2024
SIGNIFICANCE: Endoscopic screening for esophageal cancer (EC) may enable early cancer diagnosis and treatment. While optical microendoscopic technology has shown promise in improving specificity, the limited field of view () significantly reduces the...
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