AIMC Topic: Liver
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Multiclass Classification of Hepatic Anomalies with Dielectric Properties: From Phantom Materials to Rat Hepatic Tissues.
Sensors (Basel, Switzerland)
Jan 18, 2020
Open-ended coaxial probes can be used as tissue characterization devices. However, the technique suffers from a high error rate. To improve this technology, there is a need to decrease the measurement error which is reported to be more than 30% for a...
Liver tissue classification of en face images by fractal dimension-based support vector machine.
Journal of biophotonics
Jan 16, 2020
Full-field optical coherence tomography (FF-OCT) has been reported with its label-free subcellular imaging performance. To realize quantitive cancer detection, the support vector machine model of classifying normal and cancerous human liver tissue is...
Convolutional neural network-automated hepatobiliary phase adequacy evaluation may optimize examination time.
European journal of radiology
Jan 14, 2020
PURPOSE: To develop and evaluate the performance of a fully-automated convolutional neural network (CNN)-based algorithm to evaluate hepatobiliary phase (HBP) adequacy of gadoxetate disodium (EOB)-enhanced MRI. Secondarily, we explored the potential ...
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).
Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks.
Medical physics
Jan 1, 2020
PURPOSE: Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissue...
Precise hepatectomy in the intelligent digital era.
International journal of biological sciences
Jan 1, 2020
In the past 20 years, the concept of surgery has undergone profound changes. Surgical practice has shifted from emphasizing the complete elimination of lesions to achieving optimal rehabilitation in patients. Collaborative optimization of surgery con...
Comparison of the predictive outcomes for anti-tuberculosis drug-induced hepatotoxicity by different machine learning techniques.
Computer methods and programs in biomedicine
Dec 27, 2019
BACKGROUND: The study compared the predictive outcomes of artificial neural network, support vector machine and random forest on the occurrence of anti-tuberculosis drug-induced hepatotoxicity.
Gene Frequency
Adult
Polymorphism, Genetic
Sensitivity and Specificity
Chemical and Drug Induced Liver Injury
Liver
Reproducibility of Results
Male
Drug Discovery
Humans
Taiwan
Middle Aged
Neural Networks, Computer
ROC Curve
Risk Factors
Antitubercular Agents
Machine Learning
Genomics
Aged
Tuberculosis
Female
Genotype
Aged, 80 and over
Support Vector Machine
A novel machine learning based computational framework for homogenization of heterogeneous soft materials: application to liver tissue.
Biomechanics and modeling in mechanobiology
Dec 10, 2019
Real-time simulation of organs increases comfort and safety for patients during the surgery. Proper generalized decomposition (PGD) is an efficient numerical method with coordinate errors below 1 mm and response time below 0.1 s that can be used for ...
Discovery and annotation of novel microRNAs in the porcine genome by using a semi-supervised transductive learning approach.
Genomics
Dec 6, 2019
Despite the broad variety of available microRNA (miRNA) prediction tools, their application to the discovery and annotation of novel miRNA genes in domestic species is still limited. In this study we designed a comprehensive pipeline (eMIRNA) for miR...
Deep learning enables pathologist-like scoring of NASH models.
Scientific reports
Dec 5, 2019
Non-alcoholic fatty liver disease (NAFLD) and the progressive form of non-alcoholic steatohepatitis (NASH) are diseases of major importance with a high unmet medical need. Efficacy studies on novel compounds to treat NAFLD/NASH using disease models a...
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