Sfoglia per Soggetto "artificial neural network"
Items 1-18 di 18
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Accuracy and Calibration of Computational Approaches for Inpatient Mortality Predictive Modeling
(2016)Electronic Health Record (EHR) data can be a key resource for decision-making support in clinical practice in the "big data" era. The complete database from early 2012 to late 2015 involving hospital admissions to Inselspital ... -
Application of artificial neural networks for natural gas consumption forecasting
(2020)The present research study explores three types of neural network approaches for forecasting natural gas consumption in fifteen cities throughout Greece; a simple perceptron artificial neural network (ANN), a state-of-the-art ... -
Artificial Intelligence in Cardiology—A Narrative Review of Current Status
(2022)Artificial intelligence (AI) is an integral part of clinical decision support systems (CDSS), offering methods to approximate human reasoning and computationally infer decisions. Such methods are generally based on medical ... -
Comparison of the performance of stochastic models in forecasting daily dissolved oxygen data in dam-Lake Thesaurus
(2016)This study presents the development and validation of three different stochastic models on the basis of (a) their efficiency to forecast and (b) their ability to utilize auxiliary environmental information. The three models ... -
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification
(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 ... -
Evaluation of a Numerical, Real-Time Ultrasound Imaging Model for the Prediction of Litter Size in Pregnant Sows, with Machine Learning
(2022)The present study aimed to evaluate the accuracy of a numerical model, quantifying real-time ultrasonographic (RTU) images of pregnant sows, to predict litter size. The time of the test with the least error was also ... -
Hidden neural networks for transmembrane protein topology prediction
(2021)Hidden Markov Models (HMMs) are amongst the most successful methods for predicting protein features in biological sequence analysis. However, there are biological problems where the Markovian assumption is not sufficient ... -
Intelligent visual localization of wireless capsule endoscopes enhanced by color information
(2017)Wireless capsule endoscopy (WCE) is performed with a miniature swallowable endoscope enabling the visualization of the whole gastrointestinal (GI) tract. One of the most challenging problems in WCE is the localization of ... -
Knee Injury Detection Using Deep Learning on MRI Studies: A Systematic Review
(2022)The improved treatment of knee injuries critically relies on having an accurate and costeffective detection. In recent years, deep-learning-based approaches have monopolized knee injury detection in MRI studies. The aim ... -
Look-behind fully convolutional neural network for computer-aided endoscopy
(2019)In this paper, we propose a novel Fully Convolutional Neural Network (FCN) architecture aiming to aid the detection of abnormalities, such as polyps, ulcers and blood, in gastrointestinal (GI) endoscopy images. The proposed ... -
Low complexity regions in the proteins of prokaryotes perform important functional roles and are highly conserved
(2019)We provide the first high-throughput analysis of the properties and functional role of Low Complexity Regions (LCRs) in more than 1500 prokaryotic and phage proteomes. We observe that, contrary to a widespread belief based ... -
Minutely active power forecasting models using neural networks
(2020)Power forecasting is an integral part of the Demand Response design philosophy for power systems, enabling utility companies to understand the electricity consumption patterns of their customers and adjust price signals ... -
Multilayer Feed Forward Models in Groundwater Level Forecasting Using Meteorological Data in Public Management
(2018)Managing the groundwater resources is very vital for human life. This research proposes a methodology for predicting the groundwater levels which can be very valuable in water resources management. This study investigates ... -
Pose recognition using convolutional neural networks on omni-directional images
(2018)Convolutional neural networks (CNNs) are used frequently in several computer vision applications. In this work, we present a methodology for pose classification of binary human silhouettes using CNNs, enhanced with image ... -
Prostate Volume as a Risk Factor for Lower Urinary Tract Symptoms: The Quest Continues
(2016)[No abstract available] -
The use of an artificial neural network in the evaluation of the extracorporeal shockwave lithotripsy as a treatment of choice for urinary lithiasis
(2022)Objective: Artificial neural networks (ANNs) are widely applied in medicine, since they substantially increase the sensitivity and specificity of the diagnosis, classification, and the prognosis of a medical condition. In ... -
Video-Based Eye Blink Identification and Classification
(2022)Blink detection and classification can provide a very useful clinical indicator, because of its relation with many neurological and ophthalmological conditions. In this work, we propose a system that automatically detects ... -
Why has metabolomics so far not managed to efficiently contribute to the improvement of assisted reproduction outcomes? The answer through a review of the best available current evidence
(2021)Metabolomics emerged to give clinicians the necessary information on the competence, in terms of physiology and function, of gametes, embryos, and the endometrium towards a targeted infertility treatment, namely, assisted ...