Hybrid ensemble deep learning model for advancing breast cancer detection and classification in clinical applications
Being the most common type of cancer worldwide, and affecting over 2.3 million women,
breast cancer poses a significant health threat. Although survival rates have improved …
breast cancer poses a significant health threat. Although survival rates have improved …
Intelligent Breast Mass Classification Approach Using Archimedes Optimization Algorithm with Deep Learning on Digital Mammograms
M Basheri - Biomimetics, 2023 - mdpi.com
Breast cancer (BC) has affected many women around the world. To accomplish the
classification and detection of BC, several computer-aided diagnosis (CAD) systems have …
classification and detection of BC, several computer-aided diagnosis (CAD) systems have …
Challenges to the Early Diagnosis of Breast Cancer: Current Scenario and the Challenges Ahead
Breast cancer is still a major problem for medical research, science, and society. Breast
cancer is the most common form of cancer among women and has a high rate of mortality …
cancer is the most common form of cancer among women and has a high rate of mortality …
[HTML][HTML] Enhancing breast cancer segmentation and classification: An Ensemble Deep Convolutional Neural Network and U-net approach on ultrasound images
Breast cancer is a condition where the irregular growth of breast cells occurs uncontrollably,
leading to the formation of tumors. It poses a significant threat to women's lives globally …
leading to the formation of tumors. It poses a significant threat to women's lives globally …
[PDF][PDF] Machine learning models for statistical analysis.
Compared to traditional statistical models, Machine Learning (ML) algorithms provide the
ability to interpret, understand and summarize patterns and regularities in observed data for …
ability to interpret, understand and summarize patterns and regularities in observed data for …
A Hybrid Deep Learning based Classification of Brain Lesion Classification in CT Image using Convolutional Neural Networks
RS Priya, KL Narayanan, BV Nirmala… - … and Smart Energy …, 2023 - ieeexplore.ieee.org
In this effort, a deep learning technique for segmenting and detecting hemorrhagic lesions
on brain CT images is proposed. This study intends to develop a framework for deep …
on brain CT images is proposed. This study intends to develop a framework for deep …
Automated Pneumonia Classification Using DensePneumoNet in Chest CT Scans
“DensePneumoNct” is a specialized deep learning algorithm designed for accurate and
efficient detection of pneumonia from CT chest images. Leveraging the DenseNet …
efficient detection of pneumonia from CT chest images. Leveraging the DenseNet …
Revolutionizing Breast Cancer Diagnosis: A Concatenated Precision through Transfer Learning in Histopathological Data Analysis
D Jaganathan, S Balasubramaniam, V Sureshkumar… - Diagnostics, 2024 - mdpi.com
Breast cancer remains a significant global public health concern, emphasizing the critical
role of accurate histopathological analysis in diagnosis and treatment planning. In recent …
role of accurate histopathological analysis in diagnosis and treatment planning. In recent …
[PDF][PDF] Deep Learning Based Feature Discriminability Boosted Concurrent Metal Surface Defect Detection System Using YOLOv-5s-FRN
R Vengaloor, R Muralidhar - cell, 2024 - iajit.org
Computer vision and deep learning techniques are the most emerging technologies in this
era. Both of these can greatly raise the rate at which defects on metal surfaces are identified …
era. Both of these can greatly raise the rate at which defects on metal surfaces are identified …
A Deep Learning Approach Towards Student Performance Prediction in Online Courses: Challenges Based on a Global Perspective
Analyzing and evaluating students' progress in any learning environment is stressful and
time consuming if done using traditional analysis methods. This is further exasperated by the …
time consuming if done using traditional analysis methods. This is further exasperated by the …