analiza aiqbench
This study demonstrates a practical application of Convolutional Neural Networks (CNNs) for dental image processing, where supervised learning on radiographic datasets enables high-accuracy detection of cavities and teeth. The system functions as an assistive tool to streamline diagnostic workflows rather than replacing clinical judgment, highlighting the ongoing integration of computer vision into specialized medical domains.
FFCLRP helps dentists read x-rays, speeding up diagnosis
Researchers at USP’s FFCLRP and School of Dentistry developed AI to analyze x-rays, assisting dentists in identifying teeth and cavities with high accuracy, as published in PLOS Digital Health.
A study published in the journal PLOS Digital Health demonstrates the accuracy of an artificial intelligence system developed at USP in Ribeirão Preto for identifying teeth and detecting cavities in x-rays. Approximately 30 researchers from the Faculty of Philosophy, Sciences and Languages at Ribeirão Preto and the School of Dentistry of Ribeirão Preto are collaborating within the Interdisciplinary Research Group in Digital Dentistry (InReDD) on the project. According to professor Alessandra Alaniz Macedo, the technology…
Extras afișat conform termenilor RSS ai publicației · 75 cuvinte · textul integral și figurile sunt pe site-ul publicației
Subiecte conexe
How Cornerstone OnDemand cut database diagnosis by 78% with Amazon Bedrock
AWS · 7 oct. 2026
News Archive 2026
Quantum Computing Report · 25 iul. 2026
Performance Profiling on AMD GPUs – Part 5: Profiling-Driven Kernel Optimization with an AI Code-Assist Tool
AMD · 16 iul. 2026
Sensor Diagnosis for Fuel and Emissions Monitoring in Heavy-Duty Diesel Vehicles
arXiv · 16 oct. 2026