Genetic algorithm pruning of probabilistic neural networks in medical disease estimation
A hybrid model consisting of an Artificial Neural Network (ANN) and a Genetic Algorithm
procedure for diagnostic risk factors selection in Medicine is proposed in this paper. A …
procedure for diagnostic risk factors selection in Medicine is proposed in this paper. A …
Medical disease prediction using artificial neural networks
This study examines a variety of artificial neural network (ANN) models in terms of their
classification efficiency in an orthopedic disease, namely osteoporosis. Osteoporosis risk …
classification efficiency in an orthopedic disease, namely osteoporosis. Osteoporosis risk …
[HTML][HTML] Predictive modelling of the LD50 activities of coumarin derivatives using neural statistical approaches: Electronic descriptor-based DFT
R Hmamouchi, M Larif, S Chtita, A Adad… - Journal of Taibah …, 2016 - Elsevier
A study of structure–activity relationship (QSAR) was performed on a set of 30 coumarin-
based molecules. This study was performed using multiple linear regressions (MLRs) and …
based molecules. This study was performed using multiple linear regressions (MLRs) and …
[PDF][PDF] Artificial neural networks for estimation of dementias types
D Mantzaris, M Vrizas, S Trougkakos, E Priska… - Artificial …, 2014 - researchgate.net
In the last decades, there is a vivid interest of many researchers about algorithms with
natural procedure similarities. Artificial Neural Networks (ANNs) are wide known algorithms …
natural procedure similarities. Artificial Neural Networks (ANNs) are wide known algorithms …
[PDF][PDF] Solar radiation: Cloudiness forecasting using a soft computing approach.
VH Mantzari, DH Mantzaris - Artif. Intell. Res., 2013 - academia.edu
Solar energy is one of the most important energy sources with increasing penetration into
the power supply systems of many countries, due to the reduced environmental impact of its …
the power supply systems of many countries, due to the reduced environmental impact of its …
A non-symbolic implementation of abdominal pain estimation in childhood
The abdominal pain is a very common disease in childhood, which lurks complications.
Pediatric surgeons have to estimate at least 15 clinical and laboratory factors in order to …
Pediatric surgeons have to estimate at least 15 clinical and laboratory factors in order to …
The estimation of corporate liquidity management using artificial neural networks
In this paper computational intelligence techniques are applied based on Artificial Neural
Networks (ANNs) in order to investigate the liquidity performance of Greek listed firms. The …
Networks (ANNs) in order to investigate the liquidity performance of Greek listed firms. The …
Artificial neural networks with a signed-rank objective function and applications
In this paper, we propose to analyze artificial neural networks using a signed-rank objective
function as the error function. We prove that the variance of the gradient of the learning …
function as the error function. We prove that the variance of the gradient of the learning …
A machine learning approach on classifying orthopedic patients based on their biomechanical features
A person's orthopedic health condition can be detected from his biomechanical features.
Now a days, disease prediction can be done automatically. Application of machine learning …
Now a days, disease prediction can be done automatically. Application of machine learning …
A hierarchical, ontology-driven Bayesian concept for ubiquitous medical environments-A case study for pulmonary diseases
The present paper extends work on an existing computer-based Decision Support System
(DSS) that aims to provide assistance to physicians as regards to pulmonary diseases. The …
(DSS) that aims to provide assistance to physicians as regards to pulmonary diseases. The …