AIMC Topic: Liver Diseases
Clear Filters Showing 51 to 60 of 92 articles
Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.
Bio Systems
Aug 11, 2020
The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis and genome analysis. The deep learning based optimization models utilize to predict the liver cance...
Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach.
European radiology experimental
Apr 6, 2020
BACKGROUND: To evaluate whether machine learning algorithms allow the prediction of Child-Pugh classification on clinical multiphase computed tomography (CT).
Applying Machine Learning in Liver Disease and Transplantation: A Comprehensive Review.
Hepatology (Baltimore, Md.)
Mar 6, 2020
Machine learning (ML) utilizes artificial intelligence to generate predictive models efficiently and more effectively than conventional methods through detection of hidden patterns within large data sets. With this in mind, there are several areas wi...
Model to Predict Progression of Liver Disease in Heavy Drinkers Is Useful Today and Supports the Future of Deep Learning.
Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Feb 13, 2020
Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.
European radiology
Feb 13, 2020
OBJECTIVES: To evaluate whether the liver and spleen volumetric indices, measured on portal venous phase CT images, could be used to assess liver fibrosis severity in chronic liver disease.
Liver lesion localisation and classification with convolutional neural networks: a comparison between conventional and spectral computed tomography.
Biomedical physics & engineering express
Jan 30, 2020
PURPOSE: To evaluate the benefit of the additional available information present in spectral CT datasets, as compared to conventional CT datasets, when utilizing convolutional neural networks for fully automatic localisation and classification of liv...
A two-step automated quality assessment for liver MR images based on convolutional neural network.
European journal of radiology
Jan 9, 2020
PURPOSE: To propose an automatic approach based on a convolutional neural network (CNN) to evaluate the quality of T2-weighted liver magnetic resonance (MR) images as nondiagnostic (ND) or diagnostic (D).
Liver disease screening based on densely connected deep neural networks.
Neural networks : the official journal of the International Neural Network Society
Nov 11, 2019
Liver disease is an important public health problem. Liver Function Tests (LFT) is the most achievable test for liver disease diagnosis. Most liver diseases are manifested as abnormal LFT. Liver disease screening by LFT data is helpful for computer a...
Application of Artificial Intelligence to Gastroenterology and Hepatology.
Gastroenterology
Oct 5, 2019
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...
How will artificial intelligence affect diagnosis and treatment of liver disease?
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Jul 14, 2019
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