Mechanical properties of additively manufactured lattice structures designed by deep learning DOI
Nurullah Yüksel, Oğulcan Eren, Hüseyin Rıza Börklü

et al.

Thin-Walled Structures, Journal Year: 2023, Volume and Issue: 196, P. 111475 - 111475

Published: Dec. 13, 2023

Language: Английский

Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts DOI
Yutao Yang, Huiling Chen, Ali Asghar Heidari

et al.

Expert Systems with Applications, Journal Year: 2021, Volume and Issue: 177, P. 114864 - 114864

Published: March 11, 2021

Language: Английский

Citations

882

Protein nanoparticles in drug delivery: animal protein, plant proteins and protein cages, albumin nanoparticles DOI Creative Commons
Ehsan Kianfar

Journal of Nanobiotechnology, Journal Year: 2021, Volume and Issue: 19(1)

Published: May 29, 2021

Abstract In this article, we will describe the properties of albumin and its biological functions, types sources that can be used to produce nanoparticles, methods producing therapeutic applications importance nanoparticles in production pharmaceutical formulations. view increasing use Abraxane approval for treatment several cancer during final stages clinical trials other cancers, evaluate it compare effectiveness with conventional non formulations chemotherapy Paclitaxel is paid. examine role animal proteins Nano medicine various benefits these biomolecules preparation drug delivery carriers characteristics plant protein cages their potentials diagnosis treatment. Finally, advantages disadvantages are mentioned, as well

Language: Английский

Citations

325

A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique DOI Creative Commons
Abeer Saber,

Mohamed Sakr,

Osama M. Abo-Seida

et al.

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 71194 - 71209

Published: Jan. 1, 2021

Breast cancer (BC) is one of the primary causes death among women. Early detection BC allows patients to receive appropriate treatment, thus increasing possibility survival. In this work, a new deep-learning (DL) model based on transfer-learning (TL) technique developed efficiently assist in automatic and diagnosis suspected area two techniques namely 80-20 cross-validation. DL architectures are modeled be problem-specific. TL uses knowledge gained during solving problem another relevant problem. proposed model, features extracted from mammographic image analysis- society (MIAS) dataset using pre-trained convolutional neural network (CNN) architecture such as Inception V3, ResNet50, Visual Geometry Group networks (VGG)-19, VGG-16, Inception-V2 ResNet. Six evaluation metrics for evaluating performance terms accuracy, sensitivity, specificity, precision, F-score, under ROC curve (AUC) has been chosen. Experimental results show that VGG16 powerful by classifying mammogram breast images with overall AUC 98.96%, 97.83%, 99.13%, 97.35%, 97.66%, 0.995, respectively method 98.87%, 97.27%, 98.2%, 98.84%, 98.04%, 0.993 10-fold cross-validation method.

Language: Английский

Citations

292

Grasshopper Optimization Algorithm: Theory, Variants, and Applications DOI Creative Commons
Yassine Meraihi, Asma Benmessaoud Gabis, Seyedali Mirjalili

et al.

IEEE Access, Journal Year: 2021, Volume and Issue: 9, P. 50001 - 50024

Published: Jan. 1, 2021

Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired by the foraging and swarming behavior of grasshoppers in nature. The GOA has been successfully applied to solve various optimization problems several domains demonstrated its merits literature. This paper proposes comprehensive review based on more than 120 scientific articles published leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, others. It provides variants, including multi-objective hybrid variants. also discusses main applications fields such as scheduling, economic dispatch, feature selection, load frequency control, distributed generation, wind energy system, other engineering problems. Finally, some possible future research directions this area.

Language: Английский

Citations

232

Magnetic Nanoparticles in Targeted Drug Delivery: a Review DOI
Ehsan Kianfar

Journal of Superconductivity and Novel Magnetism, Journal Year: 2021, Volume and Issue: 34(7), P. 1709 - 1735

Published: June 17, 2021

Language: Английский

Citations

187

Multilevel threshold image segmentation with diffusion association slime mould algorithm and Renyi's entropy for chronic obstructive pulmonary disease DOI
Songwei Zhao, Pengjun Wang, Ali Asghar Heidari

et al.

Computers in Biology and Medicine, Journal Year: 2021, Volume and Issue: 134, P. 104427 - 104427

Published: May 6, 2021

Language: Английский

Citations

111

Boosting whale optimization with evolution strategy and Gaussian random walks: an image segmentation method DOI
Abdelazim G. Hussien, Ali Asghar Heidari, Xiaojia Ye

et al.

Engineering With Computers, Journal Year: 2022, Volume and Issue: 39(3), P. 1935 - 1979

Published: Jan. 27, 2022

Language: Английский

Citations

104

Simulated annealing-based dynamic step shuffled frog leaping algorithm: Optimal performance design and feature selection DOI
Yun Liu, Ali Asghar Heidari, Zhennao Cai

et al.

Neurocomputing, Journal Year: 2022, Volume and Issue: 503, P. 325 - 362

Published: June 28, 2022

Language: Английский

Citations

95

Image segmentation of Leaf Spot Diseases on Maize using multi-stage Cauchy-enabled grey wolf algorithm DOI
Helong Yu,

Jiuman Song,

Chengcheng Chen

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 109, P. 104653 - 104653

Published: Jan. 20, 2022

Language: Английский

Citations

89

Multi-threshold image segmentation using a multi-strategy shuffled frog leaping algorithm DOI
Yi Chen, Mingjing Wang, Ali Asghar Heidari

et al.

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 194, P. 116511 - 116511

Published: Jan. 12, 2022

Language: Английский

Citations

73