Interview with Daniel Golden, Director of Machine Learning, Arterys

Questions covered:
• Give me an overview of your work at Arterys
• How did you begin your work in AI and healthcare and what motivates you to stay in this space?
• How are you using AI for good?
• What problems are you trying to solve with AI, and what are the main challenges you’re currently facing in your work?
• There are concerns of AI infringing on our data and being a risk to privacy. As vast amounts of data are collected in healthcare, how are you ensuring data is handled securely?
• What other industries do you think will benefit from your current work, and where are you most excited to see the impact?
• Would you advise a career in AI, and what are the key skills that you think are needed for such roles?

Daniel Golden, Director of Machine Learning at Arterys

Dan is the Director of Machine Learning at Arterys, a startup focused on streamlining the practice of medical image interpretation and post-processing. After receiving a PhD in Electrical Engineering from Stanford, he stayed for a postdoc, focusing on using machine learning to predict outcomes and disease characteristics in cancer patients. From there, he joined CellScope, where he founded a machine learning team that used the then-nascent field of Deep Learning to diagnose ear disease and streamline the process of recording ear exams at home. He moved to Arterys to found their machine learning team in 2015.

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