An Artificial Neural Networks Feature Extraction Approach to Predict Nephrolithiasis (Kidney Stones) Based on KUB Ultrasound Imaging

Utilizing Support Vector Machine Algorithm and Feature Reduction for Accurate Breast Cancer Detection An Exploration of Normalization and Hyperparameter Tuning Techniques

“…In a similar experiment, Yang et al [5] constructed an astounding multiple heartbeats categorization model based on convolutional neural networks and bidirectional extended short-term memory. Sumana et al [6] established an artificial neural network-based technique for identifying nephrolithiasis with KUB ultrasound imaging, whereas Gunasundari et al [6] designed a deep convolutional neural network for locating liver lesions with abdominal CT data.…”

“…As people may cope with ambiguous assessments, automated breast cancer screening applying machine learning has developed as a practical technique to enhance diagnostic accuracy [3][4][5]. A study comparing machine learning with human analysis found that machine learning obtained an accuracy of 91.1%, topping even the highly trained physicians at 79.97% [6].…”

Utilizing Support Vector Machine Algorithm and Feature Reduction for Accurate Breast Cancer Detection An Exploration of Normalization and Hyperparameter Tuning Techniques

“…In a similar experiment, Yang et al [5] constructed an astounding multiple heartbeats categorization model based on convolutional neural networks and bidirectional extended short-term memory. Sumana et al [6] established an arti�icial neural network-based technique for identifying nephrolithiasis with KUB ultrasound imaging, whereas Gunasundari et al [6] designed a deep convolutional neural network for locating liver lesions with abdominal CT data.…”