[PDF] Top 20 Evaluación de Acidez en La Lixiviación de Minerales de Cobre
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Application of artificial neural network model in diagnosis of Alzheimer’s disease
... Although researchers have revealed a great deal con- cerning AD, much is yet to be discovered about the pre- cise pathogenesis, owing to its complex causes involving genetic, environmental and metabolic factors. Wide ... See full document
7
<p>Artificial Neural Network Model for Liver Cirrhosis Diagnosis in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma</p>
... non-invasive diagnosis of LC has focused on the use of transient elastography (TE) or scor- ing ...11 model for end-stage liver disease (MELD), 12 albu- min-bilirubin (ALBI), 13 aspartate ... See full document
6
Diagnosis Of Alzheimer’s And Parkinson’s Disease Using Artificial Neural Network
... They have trouble to express their feelings through proper communication. This time the patients need assistance from other individual for the daily routines too. The patients also feel difficulty in sitting, walking and ... See full document
5
An application of artificial neural network classifier for medical diagnosis
... brain. Neural networks are based around simplified models of biological ...powerful Artificial Intelligence (AI) techniques that have the capability to learn and memorise a set of data and construct weight ... See full document
25
Automatic Heart Disease Diagnosis System Based on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) Approaches
... heart disease has become one of the most prevalent diseases which people are being suffered ...the diagnosis of it and result in delay in correct diagnosis ...heart disease is an essential ... See full document
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DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network
... AI: Artificial Intelligence; ANN: Artificial Neural Network; AUC: Area under the ROC curve; CAD: Computer Aided Diagnosis; CNN: Convolutional neural network; CWT: ... See full document
8
Artificial Intelligence in Diagnosing Tuberculosis: A Review
... proposed model gave good results and agreed with the doctor’s opinion ...the disease. There are twenty- four diagnostic parameters in the neural network, which are divided into five ...The ... See full document
5
Application of Artificial Neural Network in the Ratio Prediction of Axis Bank
... BPNN model would provide assistance to finding the financial viability of the ...propagation neural network endeavors to predict the financial ratios expressing the position of a firm to regulate the ... See full document
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Application of Artificial Neural Network in miRNA Biomarker Selection and Precise Diagnosis of Colorectal Cancer
... early diagnosis of colorectal cancer (CRC) is associated with improved survival rates, and development of novel non-invasive, sensitive, and specific diagnostic tests is highly ...CRC diagnosis. Methods: An ... See full document
68
Neural Network Priority Use of BTS for Optimizing Telecommunications in Indonesia
... designing Artificial Neural Network modeling system which will be used to determine and recognize the pattern in predicting the villages becoming the priority of installation of BTS USO for ... See full document
37
CLUSTER HEAD BASED GROUP KEY MANAGEMENT FOR MALICIOUS WIRELESS NETWORKS USING TRUST METRICS
... teaching artificial neural networks how to perform a given ...the artificial neurons are organized in layers, and send their signals “forward”, and then the errors are propagated ...the ... See full document
14
Predictive Analytics: A Review of Trends and Techniques
... of artificial intelligence and machine learning have changed the world of computation where intelligent computation techniques and algorithms are ...models. Artificial neural networks brought the ... See full document
22
Moderating effects of sex on the impact of diagnosis and amyloid positivity on verbal memory and hippocampal volume
... The Alzheimer’ s Disease Neuroimaging Initiative (ADNI) is a longitudinal, multisite AD biomarker study ...Alzheimer’s Disease Neuroimaging Initia- tive second cohort (ADNI2) and the ... See full document
6
An artificial neural network model for optimization of finished goods inventory Pages 431-438 Download PDF
... different network topography are reported in Table ...The network architecture consisting of 1 hidden layer and 10 hidden neurons, shows the best values of R 2 for both training and testing stages of the ... See full document
8
A Survey Paper on Detection and Classification of Leaf Diseases in Plants
... leaf disease in plants which are artificial neural network, Probabilistic Neural network, K means clustering for segmentation and GLCM and SGLDM for texture ...different ... See full document
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Assessing cognition and daily function in early dementia using the cognitive-functional composite: findings from the Catch-Cog study cohort
... (1) Alzheimer Center Amsterdam, Amsterdam UMC, location VU University Medical Center, The Netherlands (n = 102); (2) Alzheimer Center Erasmus Medical Center (EMC, n = 14), Rotterdam, The Netherlands; (3) ... See full document
6
Application of Artificial Neural Network for Modeling the Flash Land Dimensions in the Forging Dies
... the network becomes stabilized or the total error between the target and the output values is reduced to the given level (according to the selected criterion), that is, until ... See full document
249
Andreassen and Artificial Neural Network Models Development for Fatality Prediction with Accessibility Aspect on Regency Area Cluster in West Java Province, Indonesia
... prediction model by developing Andreassen and Artificial Neural Network models in order to gain accurate fatality data fit with Indonesian condition, especially in the Province of West ... See full document
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Neural Network based Fault Diagnosis in Analog Electronic Circuit using Polynomial Curve Fitting
... Fig 2: Proposed model of artificial neural network for the fault diagnosis in analog circuits X1.......Xn represents the coefficients of the polynomial fitted to the output frequency res[r] ... See full document
137
An Application of ANN Model with Bayesian Regularization Learning Algorithm for Computing the Operating Frequency of C-Shaped Patch Antennas
... It is well known that current advancements in wireless communication technology have led to increase the use of PAs; hence, simple models should be utilized to analyze their performances such as bandwidth and operating ... See full document
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