European Congress of Radiology 2020

A comparison of lung nodule detection sensitivity of deep learning algorithms in comparison with 3 radiologists of varying experience levels

Krishna Chaitany Kaluva, Suthirth Vaidya, Vasanathakumar Venugopal, Sriram Rajan, Pratibha Shad, Vidur Mahajan, Harsh Mahajan, Adarsh Raj, Shilpy Upadhyay

Evidence and Research

Research Presentation Session

RPS 105 - Artificial intelligence and machine learning of the lungs

‍

Read the original post
Schedule demo
Take a look at related news on this category...

Journal of Clinical Oncology
May 25, 2020
Deep learning-based predictive imaging biomarker model for EGFR mutation status in non-small cell lung cancer from CT imaging
Evidence and Research
European Congress of Radiology 2020
July 15, 2020
Takeaways from the validation of an AI-based malignancy likelihood estimation for lung cancer screening when used on routine CT studies in a tertiary care hospital
Evidence and Research
European Congress of Radiology 2020
July 15, 2020
Establishing Normative Liver Volume and Attenuation for the Population of a Large Developing Country Using Deep Learning – A Retrospective Study of 1,800 CT Scans
Evidence and Research

Predible Health Private Limited

contact@predible.com

Bangalore, India

Home
LungIQ
LungIQ for COVID19
LungIQ for Patients
Resources
About us
Contact
Terms of Service
Privacy Policy
Refund Policy