Automated brain tumor detection using machine learning: A bibliometric review
R Hossain, RB Ibrahim, HB Hashim - World neurosurgery, 2023 - Elsevier
To develop a research overview of brain tumor classification using machine learning, we
conducted a systematic review with a bibliometric analysis. Our systematic review and …
conducted a systematic review with a bibliometric analysis. Our systematic review and …
[HTML][HTML] Maize disease identification based on optimized support vector machine using deep feature of DenseNet201
In recent times, maize diseases have become widespread globally, adversely impacting
agricultural productivity and causing significant financial losses. Recognizing these …
agricultural productivity and causing significant financial losses. Recognizing these …
Bayesian optimization with support vector machine model for parkinson disease classification
Parkinson's disease (PD) has become widespread these days all over the world. PD affects
the nervous system of the human and also affects a lot of human body parts that are …
the nervous system of the human and also affects a lot of human body parts that are …
Fecnet: A neural network and a mobile app for covid-19 recognition
Abstract COVID-19 has caused over 6.35 million deaths and over 555 million confirmed
cases till 11/July/2022. It has caused a serious impact on individual health, social and …
cases till 11/July/2022. It has caused a serious impact on individual health, social and …
Optimal extreme learning machine for diagnosing brain tumor based on modified sailfish optimizer
This study proposes a hierarchical automated methodology for detecting brain tumors in
Magnetic Resonance Imaging (MRI), focusing on preprocessing images to improve quality …
Magnetic Resonance Imaging (MRI), focusing on preprocessing images to improve quality …
Intelligent lung cancer MRI prediction analysis based on cluster prominence and posterior probabilities utilizing intelligent Bayesian methods on extracted gray-level …
Lung cancer is the second foremost cause of cancer due to which millions of deaths occur
worldwide. Developing automated tools is still a challenging task to improve the prediction …
worldwide. Developing automated tools is still a challenging task to improve the prediction …
Integrating spectral and image information for prediction of cottonseed vitality
Q Li, W Zhou, H Zhang - Frontiers in Plant Science, 2023 - frontiersin.org
Cotton plays a significant role in people's lives, and cottonseeds serve as a vital assurance
for successful cotton cultivation and production. Premium-quality cottonseeds can …
for successful cotton cultivation and production. Premium-quality cottonseeds can …
Prediction model of radiotherapy outcome for Ocular Adnexal Lymphoma using informative features selected by chemometric algorithms
M Zhou, J Wang, J Shi, G Zhai, X Zhou, L Ye… - Computers in Biology …, 2024 - Elsevier
Abstract Background: Ocular Adnexal Lymphoma (OAL) is a non-Hodgkin's lymphoma that
most often appears in the tissues near the eye, and radiotherapy is the currently preferred …
most often appears in the tissues near the eye, and radiotherapy is the currently preferred …
A novel myocarditis detection combining deep reinforcement learning and an improved differential evolution algorithm
Myocarditis is a serious cardiovascular ailment that can lead to severe consequences if not
promptly treated. It is triggered by viral infections and presents symptoms such as chest pain …
promptly treated. It is triggered by viral infections and presents symptoms such as chest pain …
Intelligent Bayesian Inference for Multiclass Lung Infection Diagnosis: Network Analysis of Ranked Gray Level Co-occurrence (GLCM) Features
RNM Khan, A Majid, SO Shim, S Habibullah… - New Generation …, 2024 - Springer
Deep learning-powered AI tools offer significant potential to improve COVID-19 lung
infection diagnosis. This study proposes a novel AI-based image analysis method for …
infection diagnosis. This study proposes a novel AI-based image analysis method for …