AIMC Topic: Diagnosis, Computer-Assisted

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Application of Artificial Intelligence to Gastroenterology and Hepatology.

Gastroenterology
Since 2010, substantial progress has been made in artificial intelligence (AI) and its application to medicine. AI is explored in gastroenterology for endoscopic analysis of lesions, in detection of cancer, and to facilitate the analysis of inflammat...

Bag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks.

Computers in biology and medicine
Parkinson's Disease (PD) is a clinical syndrome that affects millions of people worldwide. Although considered as a non-lethal disease, PD shortens the life expectancy of the patients. Many studies have been dedicated to evaluating methods for early-...

IDRiD: Diabetic Retinopathy - Segmentation and Grading Challenge.

Medical image analysis
Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted policy to avoid ...

Clinical usefulness of a deep learning-based system as the first screening on small-bowel capsule endoscopy reading.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
BACKGROUND AND AIM: To examine whether our convolutional neural network (CNN) system based on deep learning can reduce the reading time of endoscopists without oversight of abnormalities in the capsule-endoscopy reading process.

Potential of automatic diagnosis system with linked color imaging for diagnosis of Helicobacter pylori infection.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
BACKGROUND AND AIM: It is necessary to establish universal methods for endoscopic diagnosis of Helicobacter pylori (HP) infection, such as computer-aided diagnosis. In the present study, we propose a multistage diagnosis algorithm for HP infection.

Automated diagnosis and quantitative analysis of plus disease in retinopathy of prematurity based on deep convolutional neural networks.

Acta ophthalmologica
BACKGROUND: The purpose of this study was to develop an automated diagnosis and quantitative analysis system for plus disease. The system provides a diagnostic decision but also performs quantitative analysis of the typical pathological features of t...

Retinal vascular junction detection and classification via deep neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: The retinal fundus contains intricate vascular trees, some of which are mutually intersected and overlapped. The intersection and overlapping of retinal vessels represent vascular junctions (i.e. bifurcation and crossover) ...

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning.

PloS one
The blood flow through the major vessels holds great diagnostic potential for the identification of cardiovascular complications and is therefore routinely assessed with current diagnostic modalities. Heart valves are subject to high hydrodynamic loa...