AIMC Topic: Esophagitis
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Exploration of the potential therapeutic effects and targets of Coriandrum sativum on non-erosive esophagitis based on bioinformatics and molecular dynamics simulation.
Scientific reports
May 31, 2025
Gastroesophageal reflux disease (GERD) is one of the most frequently diagnosed gastrointestinal disorders, adversely affecting quality of life. Coriandrum sativum has been shown to effectively promote gastrointestinal motility, alleviate gastric disc...
An AI-assisted morphoproteomic approach is a supportive tool in esophagitis-related precision medicine.
EMBO molecular medicine
Feb 3, 2025
Esophagitis is a frequent, but at the molecular level poorly characterized condition with diverse underlying etiologies and treatments. Correct diagnosis can be challenging due to partially overlapping histological features. By proteomic profiling of...
Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 14, 2024
PURPOSE: To develop a combined radiomics and deep learning (DL) model in predicting radiation esophagitis (RE) of a grade ≥ 2 for patients with esophageal cancer (EC) underwent volumetric modulated arc therapy (VMAT) based on computed tomography (CT)...
Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images.
International journal of medical informatics
Jul 5, 2023
BACKGROUND: Gastrointestinal (GI) infections are quite common today around the world. Colonoscopy or wireless capsule endoscopy (WCE) are noninvasive methods for examining the whole GI tract for abnormalities. Nevertheless, it requires a great deal o...
Diagnosis using deep-learning artificial intelligence based on the endocytoscopic observation of the esophagus.
Esophagus : official journal of the Japan Esophageal Society
Dec 13, 2018
BACKGROUND AND AIMS: The endocytoscopic system (ECS) helps in virtual realization of histology and can aid in confirming histological diagnosis in vivo. We propose replacing biopsy-based histology for esophageal squamous cell carcinoma (ESCC) by usin...
A Randomized Phase 2 Trial of Prophylactic Manuka Honey for the Reduction of Chemoradiation Therapy-Induced Esophagitis During the Treatment of Lung Cancer: Results of NRG Oncology RTOG 1012.
International journal of radiation oncology, biology, physics
Nov 23, 2016
PURPOSE: Randomized trials have shown that honey is effective for the prevention of radiation-induced mucositis in head and neck cancer patients. Because there is no efficacious preventative for radiation esophagitis in lung cancer patients, this tri...
Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective.
International journal of radiation oncology, biology, physics
Nov 11, 2015
Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both pr...
A systematic review and meta-analysis of the utility of quantitative, imaging-based approaches to predict radiation-induced toxicity in lung cancer patients.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jul 1, 2025
BACKGROUND AND PURPOSE: To conduct a systematic review and meta-analysis of the performance of radiomics, dosiomics and machine learning in generating toxicity prediction in thoracic radiotherapy.
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