Deep Learning Tool Improves Accuracy of Lung Nodule Malignancy Detection

Deep learning tool improves accuracy of lung nodule malignancy detection

An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results.

Deep learning model estimates cancer risk of lung nodules

An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. Results of the study, which used data from large, multi-site lung cancer screening trials, were published in Radiology.

AI Deep Learning Tool Sharpens Lung Cancer Screening Accuracy

Validated on large European trials, a deep learning algorithm shows strong generalizability for lung nodule malignancy prediction in screening programs.

DL algorithm estimates lung nodule cancer risk, reduces false positives

The deep-learning (DL) tool reduced false-positive results by almost 40% and showed high cancer detection rates.

CT-Based Deep Learning Model May Reduce False Positives with Indeterminate Lung Nodules by Nearly 40 Percent

In a recent interview with Diagnostic Imaging, Noa Antonissen, M.D., and Colin Jacobs, Ph.D., discussed new research findings demonstrating robust risk stratification with a CT-based deep learning model for lung nodules as well as a 39.4 percent reduction in false positives in comparison to traditional classification.

Deep Learning Model Assesses Lung Nodule Cancer Risk

An innovative deep learning algorithm has emerged as a potential game-changer in the stratification of malignancy risks associated with pulmonary nodules. A recent study published in the esteemed journal, Radiology, indicates that this artificial intelligence-based tool not only excels in accurately identifying