A comparison of feature selection models utilizing binary particle swarm optimization and genetic algorithm in determining coronary artery disease using support …
The aim of this study is to search the efficiency of binary particle swarm optimization (BPSO)
and genetic algorithm (GA) techniques as feature selection models on determination of …
and genetic algorithm (GA) techniques as feature selection models on determination of …
Knowledge and intelligent computing system in medicine
B Pandey, RB Mishra - Computers in biology and medicine, 2009 - Elsevier
Knowledge-based systems (KBS) and intelligent computing systems have been used in the
medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning …
medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning …
One-shot learning of human activity with an MAP adapted GMM and simplex-HMM
This paper presents a novel activity class representation using a single sequence for
training. The contribution of this representation lays on the ability to train an one-shot …
training. The contribution of this representation lays on the ability to train an one-shot …
Notice of retraction: molecular diagnostic and using deep learning techniques for predict functional recovery of patients treated of cardiovascular disease
AR Junejo, Y Shen, AA Laghari, X Zhang, H Luo - IEEE Access, 2019 - ieeexplore.ieee.org
Notice of Retraction "Molecular Diagnostic and Using Deep Learning Techniques for Predict
Functional Recovery of Patients T Page 1 Notice of Retraction "Molecular Diagnostic and Using …
Functional Recovery of Patients T Page 1 Notice of Retraction "Molecular Diagnostic and Using …
A hybrid system based on information gain and principal component analysis for the classification of transcranial Doppler signals
H Uğuz - Computer methods and programs in biomedicine, 2012 - Elsevier
A transcranial Doppler (TCD) is a non-invasive, easy to apply and reliable technique which
is used in the diagnosis of various brain diseases by measuring the blood flow velocities in …
is used in the diagnosis of various brain diseases by measuring the blood flow velocities in …
[HTML][HTML] Transcranial Doppler analysis based on computer and artificial intelligence for acute cerebrovascular disease
L Gan, X Yin, J Huang, B Jia - Mathematical Biosciences and …, 2023 - aimspress.com
Cerebrovascular disease refers to damage to brain tissue caused by impaired intracranial
blood circulation. It usually presents clinically as an acute nonfatal event and is …
blood circulation. It usually presents clinically as an acute nonfatal event and is …
A hybrid of neuro-fuzzy inference system and hidden Markov Model for activity-based mobility modeling of cellphone users
The aim of this paper is to develop an activity-based travel demand model by receiving
cellular network data. Our contribution is to model the uncertainty of human behaviors and …
cellular network data. Our contribution is to model the uncertainty of human behaviors and …
A new method for diagnosis and predicting blood disorder and cancer using artificial intelligence (artificial neural networks)
M Payandeh, M Aeinfar, V Aeinfar… - International Journal of …, 2009 - ijhoscr.tums.ac.ir
This paper represents a novel use of artificial neural networks in medical science. The
proposed technique involves training a Multi Layer Perceptron (MLP)(a kind of artificial …
proposed technique involves training a Multi Layer Perceptron (MLP)(a kind of artificial …
A novel fuzzy hmm approach for human action recognition in video
K Mozafari, N Moghadam Charkari… - … Technology Week, KTW …, 2012 - Springer
Abstract Hidden Markov Model (HMM) has been used in Human Action Recognition (HAR)
since early 1980s. In this paper, an improvement of HMM using fuzzy concepts is proposed …
since early 1980s. In this paper, an improvement of HMM using fuzzy concepts is proposed …
One-sequence learning of human actions
C Orrite, M Rodríguez, M Montañés - International Workshop on Human …, 2011 - Springer
In this paper we address the problem of human action recognition from a single training
sequence per class using a modified version of the Hidden Markov Model. Inspired by …
sequence per class using a modified version of the Hidden Markov Model. Inspired by …