How Retina Physicians Can Use AI, With Natasa Jovic, RetinAI


Click here to watch the video version of this podcast.

Natasa Jovic has led marketing strategies for retina products since the launch of Visudyne. Approved by the FDA in 2002, Visudyne was the first commercially available therapy to treat wet AMD.

Today, Jovic applies her scientific background and retina experience to lead marketing and commercial operations for RetinAI, a software company that supports R&D initiatives.

As a retina specialist, OIS podcast host Firas Rahhal, MD, wanted to know: what’s the deal with AI? How can it help me in my practice? Jovic provides insight.

At present, the FDA has approved over 500 AI-enabled medical devices, most of them in radiology and cardiology. Ophthalmology has seven. Those seven products, in addition to ancillary unregulated devices, she says, have the potential to streamline workflows, expedite clinical research, and generally assist in the clinical decision-making and care management.

Listen to the podcast today to discover:
• More about Jovic’s background, which included managing Visudyne’s marketing strategy.
• AI 101: The difference between machine learning, deep learning, and AI and what each of these disciplines do.
• Why ophthalmology—and retina specifically—is an ideal therapeutic area for AI-based applications.
• The general regulatory pathways and considerations for AI-enabled medical devices and clinical decision support (CDS) software compared to traditional medical devices and CDS.
• The value of AI-based technology in streamlining intravitreal injection process and treatment decision-making.
• The direction for ophthalmology clinical trials, including the use of data to narrow inclusion criteria.
• Why AI will continue to play an integral role in drug discovery and development, and the benefits of that change.
• The details behind RetinAI’s Discovery Unity data management platform and Discovery Core for research analysis, including how they perform.

[Press Play]

RetinAI –
Natasa Jovic –
Firas Rahhal, MD –
Artificial Intelligence and Machine Learning-Enabled Medical Devices –