AIMC Topic: Gastrointestinal Diseases
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Granulomatosis with polyangiitis in Northeastern Brazil: study of 25 cases and review of the literature.
Advances in rheumatology (London, England)
Jun 28, 2018
BACKGROUND: Little has been published about the epidemiology of Granulomatosis with polyangiitis (GPA) in South America, especially in the intertropical zone, and no epidemiological data from Brazil are available. The purpose of the present study was...
Granulomatosis with Polyangiitis
Nervous System Diseases
Eye Diseases
Adrenal Cortex Hormones
Arthritis
Gastrointestinal Diseases
Brazil
Adult
Disease Progression
Cross-Sectional Studies
Lung Diseases
Humans
Male
Creatinine
Retrospective Studies
Middle Aged
Acute Kidney Injury
Skin Diseases
Female
Proteinuria
Heart Diseases
Delayed Diagnosis
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification.
IEEE transactions on medical imaging
May 15, 2018
This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only image-level, semantic labels inste...
Effects of carbohydrate mouth rinse and caffeine on high-intensity interval running in a fed state.
Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme
Dec 20, 2017
The current study aims to identify if mouth rinsing with a 6% carbohydrate mouth-rinse (CMR) solution and mouth rinsing and ingestion of caffeine (CMR+CAFF) can affect exercise performance during steady-state (SS) running and high-intensity intervals...
Into the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample.
PloS one
Dec 9, 2016
BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research w...
Identification of lesion images from gastrointestinal endoscope based on feature extraction of combinational methods with and without learning process.
Medical image analysis
May 14, 2016
The gastrointestinal endoscopy in this study refers to conventional gastroscopy and wireless capsule endoscopy (WCE). Both of these techniques produce a large number of images in each diagnosis. The lesion detection done by hand from the images above...
Acute gastrointestinal toxicity and bowel bag dose-volume parameters for preoperative radiation therapy for retroperitoneal sarcoma.
Practical radiation oncology
Dec 19, 2015
PURPOSE: Acute gastrointestinal (GI) toxicity has been studied in GI and gynecological (GYN) cancers, with volume receiving 15 Gy (V15) <830 mL, V25 <650 mL, and V45 <195 mL identified as dose constraints for the peritoneal space (bowel bag [BB]). Th...
Artificial Intelligence-Assisted Daily Quality Control System for the Histologic Diagnosis of Gastrointestinal Endoscopic Biopsies: A 1-Year Experience.
Archives of pathology & laboratory medicine
Jul 1, 2025
CONTEXT.—: Seegene Medical Foundation, one of the major clinical laboratories in South Korea, developed SeeDP, an artificial intelligence (AI)-based postanalytic daily quality control (QC) system that reassesses all gastrointestinal (GI) endoscopic b...
A multimodal deep learning model for detecting endoscopic images of near-infrared fluorescence capsules.
Biosensors & bioelectronics
Jun 15, 2025
Early screening for gastrointestinal (GI) diseases is critical for preventing cancer development. With the rapid advancement of deep learning technology, artificial intelligence (AI) has become increasingly prominent in the early detection of GI dise...
Artificial intelligence in gastroenterology: Ethical and diagnostic challenges in clinical practice.
World journal of gastroenterology
Mar 14, 2025
This article discusses the manuscript recently published in the , which explores the application of deep learning models in decision-making processes via wireless capsule endoscopy. Integrating artificial intelligence (AI) into gastrointestinal disea...
GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images.
Mathematical biosciences and engineering : MBE
Aug 15, 2024
Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpreting endoscopic images, due to their capacity to provide results equivalent to or exceeding those of ...
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