Neuro-swarm intelligent computing paradigm for nonlinear HIV infection model with CD4+ T-cells

Umar, Muhammad; Sabir, Zulqurnain; Raja, Muhammad Asif Zahoor; Aguilar, José Francisco Gómez; Amin, Fazli; Shoaib, Mohammed

doi:10.1016/j.matcom.2021.04.008

Cited by 74 publications

(18 citation statements)

References 40 publications

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“…Numerous studies have shown the usefulness of neural networks for medical diagnosis [ 2 – 4 , 30 , 31 , 40 , 42 ]. Deep neural network (DNN) consists of multiple neural network layers, i.e., hidden layers between the input and output layers.…”

Section: Classifiermentioning

confidence: 99%

Detection of Common Cold from Speech Signals using Deep Neural Network

Deb

Warule

Nair

et al. 2022

Circuits Syst Signal Process

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This paper presents a deep learning-based analysis and classification of cold speech observed when a person is diagnosed with the common cold. The common cold is a viral infectious disease that affects the throat and the nose. Since speech is produced by the vocal tract after linear filtering of excitation source information, during a common cold, its attributes are impacted by the throat and the nose. The proposed study attempts to develop a deep learning-based classification model that can accurately predict whether a person has a cold or not based on their speech. The common cold-related information is captured using Mel-frequency cepstral coefficients (MFCC) and linear predictive coding (LPC) from the speech signal. The data imbalance is handled using the sampling strategy, SMOTE–Tomek links. Then, utilizing MFCC and LPC features, a deep learning-based model is trained and then used to categorize cold speech. The performance of a deep learning-based method is compared to logistic regression, random forest, and gradient boosted tree classifiers. The proposed model is less complex and uses a smaller feature set while giving comparable results to other state-of-the-art methods. The proposed method gives an UAR of , higher than the benchmark OpenSMILE SVM result of . The study’s success will yield a noninvasive method for cold detection, which can further be extended to detect other speech-affecting pathologies.

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Section: Classifiermentioning

confidence: 99%

Detection of Common Cold from Speech Signals using Deep Neural Network

Deb

Warule

Nair

et al. 2022

Circuits Syst Signal Process

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“…The reliability of design LMANNs has been achieved in terms of mean squared errors, error histograms and regression via graphical illustrations. The stochastic numerical approach has also been used to study the HIV mathematical models in [25] , [26] , [27] . In [28] authors used Morlet wavelet neural network (MWNN) approach to investigate second order Lane-Emden equation.…”

Section: Introductionmentioning

confidence: 99%

A mathematical model of coronavirus transmission by using the heuristic computing neural networks

Sabir

Asmara

Dehraj

et al. 2023

Engineering Analysis with Boundary Elements

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“…There are deadly, contagious illnesses on every region of the planet, including HIV. HIV spreads like some of the other infections, and during the past few decades, numerous civilian casualties have been observed [ [3] , [4] , [5] ]. Lassa disease is a very severe illness that is primarily found in underdeveloped areas [ 6 ].…”

Section: Introductionmentioning

confidence: 99%