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Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools
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 …
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 …
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
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 …
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
Breast tumor segmentation and recognition from mammograms play a key role in healthcare
and treatment services. As different tumors in mammography have dissimilar densities …
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
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 …
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
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 …
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
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 …
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 …
However, inaccurate and improper diagnosis can hinder effective treatment. This paper …
A deep learning approach for robust, multi-oriented, and curved text detection
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 …
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
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 …
recommendation systems in both industry and academia. However, current POI …