Year: 2025
Type: article
Abstract: : This work presents an end-to-end deep learning-based kidney stone detection system based on a combination of Convolutional Neural Networks (CNNs) for ultrasound image processing and Random Forest for clinical data classification. The combination of the two models has an enormously improved diagnostic accuracy, reducing misclassification rates. With the use of a fusion model, the system effectively facilitates decision-making with accurate and autonomous detection. This study illustrates the advantages of multi-modal learning in medical diagnosis and aims to support healthcare professionals in early detection and treatment planning.
Authors: Ramagowni SivaKumar, Hrushikesh Reddy K V, Charan Reddy S, Surya Prakash Reddy B
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4409602203