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Put AI to work
Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA
Daniel Golden

Daniel Golden
Director, Machine Learning, Arterys

Website

Dan Golden is the director of machine learning at Arterys, a startup focused on streamlining the practice of medical image interpretation and postprocessing. Previously, he founded a machine learning team at CellScope that used the then-nascent field of deep learning to diagnose ear disease and streamline the process of recording ear exams at home and was a postdoc at Stanford, focusing on using machine learning to predict outcomes and disease characteristics in cancer patients. He holds a PhD in electrical engineering from Stanford.

Sessions

2:35pm-3:15pm Thursday, September 6, 2018
Lung cancer detection and segmentation using deep learning
Interacting with AI, Models and Methods
 Location: Yosemite BC
Secondary topics:  Health and Medicine
Daniel Golden (Arterys)
Average rating: *****
(5.00, 1 rating)
Modern radiological lung cancer screening is an entirely manual process, leading to high costs and inter-reader variability. Daniel Golden offers an overview of a deep learning-based system that automatically detects and segments lung nodules in lung CT exams and explains how it was tested for safety and efficacy. The system is FDA cleared and segments nodules as accurately as a clinician. Read more.