Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools

R Ranjbarzadeh, A Caputo, EB Tirkolaee… - Computers in biology …, 2023 - Elsevier
Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …

Review of deep learning approaches for thyroid cancer diagnosis

S Anari, N Tataei Sarshar, N Mahjoori… - Mathematical …, 2022 - Wiley Online Library
Thyroid nodule is one of the common life‐threatening diseases, and it had an increasing
trend over the last years. Ultrasound imaging is a commonly used diagnostic method for …

Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods

R Ranjbarzadeh, S Dorosti, SJ Ghoushchi… - Computers in Biology …, 2023 - Elsevier
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …

ME-CCNN: Multi-encoded images and a cascade convolutional neural network for breast tumor segmentation and recognition

R Ranjbarzadeh, S Jafarzadeh Ghoushchi… - Artificial Intelligence …, 2023 - Springer
Breast tumor segmentation and recognition from mammograms play a key role in healthcare
and treatment services. As different tumors in mammography have dissimilar densities …

HECON: Weight assessment of the product loyalty criteria considering the customer decision's halo effect using the convolutional neural networks

G Haseli, R Ranjbarzadeh, M Hajiaghaei-Keshteli… - Information …, 2023 - Elsevier
The economic pressures and increasing competition in markets have led to the CEOs of
companies being forced to make the right strategic decisions in the development of products …

[HTML][HTML] Introducing urdu digits dataset with demonstration of an efficient and robust noisy decoder-based pseudo example generator

W Khan, K Raj, T Kumar, AM Roy, B Luo - Symmetry, 2022 - mdpi.com
In the present work, we propose a novel method utilizing only a decoder for generation of
pseudo-examples, which has shown great success in image classification tasks. The …

An evolutionary crow search algorithm equipped with interactive memory mechanism to optimize artificial neural network for disease diagnosis

H Zamani, MH Nadimi-Shahraki - Biomedical Signal Processing and …, 2024 - Elsevier
Artificial neural network (ANN) is an information processing paradigm that loosely models
the thinking patterns of the human brain with specifications such as real-time learning, self …

Oral cancer detection using convolutional neural network optimized by combined seagull optimization algorithm

Q Huang, H Ding, N Razmjooy - Biomedical Signal Processing and Control, 2024 - Elsevier
Early diagnosis of oral cancer is crucial for improving patient outcomes and saving lives.
However, inaccurate and improper diagnosis can hinder effective treatment. This paper …

A deep learning approach for robust, multi-oriented, and curved text detection

R Ranjbarzadeh, S Jafarzadeh Ghoushchi, S Anari… - Cognitive …, 2024 - Springer
Automatic text localization and segmentation in a normal environment with vertical or curved
texts are core elements of numerous tasks comprising the identification of vehicles and self …

Point-of-interest preference model using an attention mechanism in a convolutional neural network

AB Kasgari, S Safavi, M Nouri, J Hou, NT Sarshar… - Bioengineering, 2023 - mdpi.com
In recent years, there has been a growing interest in develo** next point-of-interest (POI)
recommendation systems in both industry and academia. However, current POI …