[HTML][HTML] An automated metaheuristic-optimized approach for diagnosing and classifying brain tumors based on a convolutional neural network
Brain tumors must be classified to determine their severity and appropriate therapy. Applying
Artificial Intelligence to medical imaging has enabled remarkable developments. The …
Artificial Intelligence to medical imaging has enabled remarkable developments. The …
Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning
Brain tumors (BT), both benign and malignant, pose a substantial impact on human health
and need precise and early detection for successful treatment. Analysing magnetic …
and need precise and early detection for successful treatment. Analysing magnetic …
[HTML][HTML] Enhancing rop plus form diagnosis: an automatic blood vessel segmentation approach for newborn fundus images
Abstract Background ROP Plus Form is an eye disease that can lead to blindness, and
diagnosing it requires medical experts to manually examine the retinal condition. This task is …
diagnosing it requires medical experts to manually examine the retinal condition. This task is …
[HTML][HTML] An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms
The skin, the body's largest organ, plays a critical role in protection and regulation, making
its health essential. Skin cancer, one of the most prevalent malignancies, continues to rise …
its health essential. Skin cancer, one of the most prevalent malignancies, continues to rise …
[HTML][HTML] Deep hybrid architecture with stacked ensemble learning for binary classification of retinal disease
C Priyadharsini - Results in Engineering, 2024 - Elsevier
Purpose Early retinal disease identification is vital since symptoms are passive at initial
stages but lead to irreversible vision loss at advanced stages. Globally, a substantial …
stages but lead to irreversible vision loss at advanced stages. Globally, a substantial …
[HTML][HTML] Detection and classification on MRI images of brain tumor using YOLO NAS deep learning model
MS Mithun, SJ Jawhar - Journal of Radiation Research and Applied …, 2024 - Elsevier
If a brain tumor is not properly diagnosed, it might result in fatal consequences and major
health issues. As a result, a key component of diagnosis is the early identification of brain …
health issues. As a result, a key component of diagnosis is the early identification of brain …
[HTML][HTML] Brain tumor detection across diverse MR images: An automated triple-module approach integrating reduced fused deep features and machine learning
Y Pande, J Chaki - Results in Engineering, 2025 - Elsevier
Brain tumors pose a significant threat to human health due to their potential to disrupt normal
brain function. Early and accurate detection is crucial for effective treatment. This study …
brain function. Early and accurate detection is crucial for effective treatment. This study …
[HTML][HTML] Enhancing Road Traffic Flow Prediction with Improved Deep Learning using Wavelet Transforms
Precise traffic flow prediction is a central component of advancing intelligent transportation
systems, providing essential insights for optimizing traffic management, reducing travel …
systems, providing essential insights for optimizing traffic management, reducing travel …
[HTML][HTML] SAlexNet: Superimposed AlexNet using Residual Attention Mechanism for Accurate and Efficient Automatic Primary Brain Tumor Detection and Classification
Accurate classification of brain tumors is crucial for informing clinical diagnoses and guiding
patient treatment plans. It is one of the most aggressive tumors, leading to a short life …
patient treatment plans. It is one of the most aggressive tumors, leading to a short life …
Automated brain tumor recognition using equilibrium optimizer with deep learning approach on MRI images
Brain tumours (BT) affect human health owing to their location. Artificial intelligence (AI) is
intended to assist in diagnosing and treating complex diseases by combining technologies …
intended to assist in diagnosing and treating complex diseases by combining technologies …