[HTML][HTML] Bayesian optimized machine learning model for automated eye disease classification from fundus images
Eye diseases are defined as disorders or diseases that damage the tissue and related parts
of the eyes. They appear in various types and can be either minor, meaning that they do not …
of the eyes. They appear in various types and can be either minor, meaning that they do not …
[HTML][HTML] Optimizing Lung Condition Categorization through a Deep Learning Approach to Chest X-ray Image Analysis
Background: Evaluating chest X-rays is a complex and high-demand task due to the intrinsic
challenges associated with diagnosing a wide range of pulmonary conditions. Therefore …
challenges associated with diagnosing a wide range of pulmonary conditions. Therefore …
An Automated Histopathological Colorectal Cancer Multi‐Class Classification System Based on Optimal Image Processing and Prominent Features
Colorectal cancer (CRC) is characterized by the uncontrollable growth of cancerous cells
within the rectal mucosa. In contrast, colon polyps, precancerous growths, can develop into …
within the rectal mucosa. In contrast, colon polyps, precancerous growths, can develop into …
Pixel embedding for grayscale medical image classification
W Liu, N Lv, J Wan, L Wang, X Zhou - Heliyon, 2024 - cell.com
In our paper, we present an extension of text embedding architectures for grayscale medical
image classification. We introduce a mechanism that combines n-gram features with an …
image classification. We introduce a mechanism that combines n-gram features with an …
KOA-CCTNet: An Enhanced Knee Osteoarthritis Grade Assessment Framework Using Modified Compact Convolutional Transformer Model
Knee osteoarthritis (KOA) is a prevalent condition characterized by gradual progression,
resulting in observable bone alterations in X-ray images. X-rays are the preferred diagnostic …
resulting in observable bone alterations in X-ray images. X-rays are the preferred diagnostic …
[HTML][HTML] Deep Learning-Based Object Detection Strategies for Disease Detection and Localization in Chest X-Ray Images
YC Cheng, YC Hung, GH Huang, TB Chen… - …, 2024 - pmc.ncbi.nlm.nih.gov
Background and Objectives: Chest X-ray (CXR) images are commonly used to diagnose
respiratory and cardiovascular diseases. However, traditional manual interpretation is often …
respiratory and cardiovascular diseases. However, traditional manual interpretation is often …
EAH-Net: A Novel Ensemble Attention-Based Hybrid Architecture for Breast Cancer Diagnosis Utilizing Ultrasound Images
Breast cancer is a complex and often fatal malignancy in women worldwide, requiring
thorough medical examinations. Accurately detecting breast cancer is challenging due to its …
thorough medical examinations. Accurately detecting breast cancer is challenging due to its …
NewsNet: A Comprehensive Neural Network Hybrid Model for Efficient Bangla News Categorization
Through the internet, Bangla news has grown enormously within the modern era of digital
information. Every news outlet came up with its own categorizing system in order to handle …
information. Every news outlet came up with its own categorizing system in order to handle …