Artificial intelligence in the advanced diagnosis of bladder cancer-comprehensive literature review and future advancement
Artificial intelligence is highly regarded as the most promising future technology that will
have a great impact on healthcare across all specialties. Its subsets, machine learning, deep …
have a great impact on healthcare across all specialties. Its subsets, machine learning, deep …
[HTML][HTML] Artificial intelligence: A promising frontier in bladder cancer diagnosis and outcome prediction
S Borhani, R Borhani, A Kajdacsy-Balla - Critical reviews in oncology …, 2022 - Elsevier
Bladder cancer (BCa) is the most common malignancy of the urinary tract and the most
expensive malignancy to treat over the patients' lifetime. In recent years a number of studies …
expensive malignancy to treat over the patients' lifetime. In recent years a number of studies …
BreastNet18: a high accuracy fine-tuned VGG16 model evaluated using ablation study for diagnosing breast cancer from enhanced mammography images
Simple Summary Breast cancer diagnosis at an early stage using mammography is
important, as it assists clinical specialists in treatment planning to increase survival rates …
important, as it assists clinical specialists in treatment planning to increase survival rates …
Cross-domain attention-guided generative data augmentation for medical image analysis with limited data
Data augmentation is widely applied to medical image analysis tasks in limited datasets with
imbalanced classes and insufficient annotations. However, traditional augmentation …
imbalanced classes and insufficient annotations. However, traditional augmentation …
SkinNet-14: a deep learning framework for accurate skin cancer classification using low-resolution dermoscopy images with optimized training time
The increasing incidence of skin cancer necessitates advancements in early detection
methods, where deep learning can be beneficial. This study introduces SkinNet-14, a novel …
methods, where deep learning can be beneficial. This study introduces SkinNet-14, a novel …
The development of symbolic expressions for fire detection with symbolic classifier using sensor fusion data
Fire is usually detected with fire detection systems that are used to sense one or more
products resulting from the fire such as smoke, heat, infrared, ultraviolet light radiation, or …
products resulting from the fire such as smoke, heat, infrared, ultraviolet light radiation, or …
[HTML][HTML] An effective approach to address processing time and computational complexity employing modified CCT for lung disease classification
Early identification and adequate treatment can help prevent lung disorders from becoming
chronic, severe, and life-threatening. X-ray images are commonly used and an automated …
chronic, severe, and life-threatening. X-ray images are commonly used and an automated …
[HTML][HTML] Semantic segmentation of urinary bladder cancer masses from ct images: A transfer learning approach
Simple Summary Bladder cancer is a common cancer of the urinary tract, characterized by
high metastatic potential and recurrence. The research applies a transfer learning approach …
high metastatic potential and recurrence. The research applies a transfer learning approach …
Integration of deep learning network and robot arm system for rim defect inspection application
WL Mao, YY Chiu, BH Lin, CC Wang, YT Wu, CY You… - Sensors, 2022 - mdpi.com
Automated inspection has proven to be the most effective approach to maintaining quality in
industrial-scale manufacturing. This study employed the eye-in-hand architecture in …
industrial-scale manufacturing. This study employed the eye-in-hand architecture in …
Semi-supervised Bladder Tissue Classification in Multi-Domain Endoscopic Images
Objective: Accurate visual classification of bladder tissue during Trans-Urethral Resection of
Bladder Tumor (TURBT) procedures is essential to improve early cancer diagnosis and …
Bladder Tumor (TURBT) procedures is essential to improve early cancer diagnosis and …