Classification of Covid-19 misinformation on social media based on neuro-fuzzy and neural network: A systematic review

BD Ravichandran, P Keikhosrokiani - Neural Computing and Applications, 2023 - Springer
The spread of Covid-19 misinformation on social media had significant real-world
consequences, and it raised fears among internet users since the pandemic has begun …

Cervical cancer classification from pap smear images using modified fuzzy C means, PCA, and KNN

N Lavanya Devi, P Thirumurugan - IETE Journal of Research, 2022 - Taylor & Francis
Cervical cancer is having the second-highest mortality rate next to breast cancer among
women in developing countries. Early detection of the abnormality is the only way to prevent …

Heartbeat sound classification using a hybrid adaptive neuro-fuzzy inferences system (ANFIS) and artificial bee colony

P Keikhosrokiani, AB Naidu A/P Anathan… - Digital …, 2023 - journals.sagepub.com
Cardiovascular disease is one of the main causes of death worldwide which can be easily
diagnosed by listening to the murmur sound of heartbeat sounds using a stethoscope. The …

Brain tumour detection in magnetic resonance imaging using Levenberg–Marquardt backpropagation neural network

M Ghahramani, N Shiri - IET image processing, 2023 - Wiley Online Library
Magnetic resonance imaging (MRI) is a high‐quality medical image that is used to detect
brain tumours in a complex and time‐consuming manner. In this study, a back propagation …

Classification of brain tumor from magnetic resonance images using probabilistic features and possibilistic Hanman–Shannon transform classifier

P Asthana, M Hanmandlu… - International Journal of …, 2022 - Wiley Online Library
A brain tumor is considered one of the deadliest forms among all types of cancer due to its
aggressive nature leading to patients' low survival rate. Detection and classification of brain …

An adaptive neuro‐fuzzy inference system optimized by genetic algorithm for brain tumour detection in magnetic resonance images

M Ghahramani, N Shiri - IET Image Processing, 2024 - Wiley Online Library
An adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic
algorithm to classify normal and abnormal brain tumours. The classifier is fast and simple …

BrainNeuroNet: advancing brain tumor detection with hierarchical transformers and multiscale attention

S Poornam, JJR Angelina - International Journal of Information …, 2024 - Springer
Brain tumor (BT) refers to abnormal proliferation of brain tissues and accurate detection is
complex for radiologists. The accurate and early detection impact is based on the shapes …

[HTML][HTML] Automated Brain Tumor Detection using Ideal Shallow Neural Network with Artificial Jellyfish Optimization

SR Sridhar, M Akila, R Asokan - 2024 - benthamdirect.com
Introduction: Brain tumors are predicted from Magnetic Resonance Imaging (MRI) and
Computed Tomography (CT) scan images. In recent years, image processing-based …

Detection and Segmentation of Glioma Tumors Using an Improved Visual Geometry Group (IVGG) Deep Learning Structure

P Alagarsamy, VK Kalimuthu… - Brazilian Archives of …, 2025 - SciELO Brasil
Glioma brain tumors have similar textural patterns to other tumors, making their detection
and segmentation a challenging process. The approach of the Modified Tumor Detection …

Detection of meningioma tumor images using Modified Empirical Mode Decomposition (MEMD) and convolutional neural networks

S Krishnakumar, K Manivannan - Journal of Intelligent & …, 2023 - content.iospress.com
The meningioma brain tumor detection is more important than the other tumor detection
such as Glioma and Glioblastoma, due to its high severity level. The tumor pixel density of …