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Evidence in Days, Not Years: Gesund Partners With ScanDiags to Supercharge the Process of Validating Radiology AI

Gesund opens the doors to gold standard data needed to validate AI: case-specific data annotated by board-certified radiologists

Boston, MA and Berlin, Germany – WEBWIRE

Gesund, the company ensuring that medical artificial intelligence (AI) is safe and effective for all, today announced it is working with ScanDiags to advance innovation in radiology.

Radiology has emerged as a key area for Gesund because AI itself is making fast progress in the field. A study by the American College of Radiology found that clinical adoption of AI by radiologists jumped from zero in 2015 to 30 percent in 2020. Underlying clinical adoption is the creation of helpful tools which lighten the load placed upon a radiologist, like the software ScanDiags makes that is AI for augmented diagnosis from musculoskeletal MRI. Such software unburdens medical professionals from repetitive and quality-challenged work to analyze and leverage more clinical information than ever to lower health providers’ costs.

For people creating the AI tools however, healthcare stands as a uniquely complicated industry where generating algorithm performance metrics can take years. This is why Gesund is building an independent evaluation platform for clinicians and companies to validate medical AI. Purpose-built to be an intuitive and easy to use platform applicable in many scenarios, one of Gesund’s breakthrough features is access to the highest quality data needed for validating a new algorithm.

“We are creating a new way for radiologists to analyze orthopedic MRI scans by augmenting the process through the use of AI,” said Stefan Voser, CPO of ScanDiags. “Gesund is invaluable to what we are doing because it streamlines our regulatory clearance efforts by running our algorithm against case-specific data annotated by board-certified radiologists to generate regulatory-grade performance metrics within days instead of years. An enormous amount of such data is needed for AI solutions to make assessments and predictions with confidence.”

By building a compliant picks-and-shovels MLOps platform that is agnostic to the underlying AI, developers can upload or register their algorithms and share with other collaborators in remote sites while also being able to run the same algorithm on proprietary datasets shared by other parties privately, all happening within the same platform with no PHI data exposed.

“Time-to-evidence, how fast you can get performance metrics on your algorithm, has emerged as a KPI for every AI company in medicine,” observed Dr. Enes Hosgor, CEO and founder of Gesund. “That has now become our own internal KPI and we’re transforming that metric in the field of radiology.”

The news follows on the heels of a series of notable developments for the company since it debuted from stealth in March 2022. Of note, it will be exhibiting at the preeminent radiology conference RSNA and expanding its operations heading into 2023.

About Gesund
Gesund is building the highway of clinical-grade artificial intelligence.

The company connects highly curated and diverse data sets to medtech innovators so they can more quickly and efficiently validate AI that’s effective and safe for clinical settings. It’s designed from the ground up to work in high compliance environments with no cloud access and to be used by physicians, researchers and other medical stakeholders through a simple low-code interface.

The company was founded by Enes Hosgor, Ph.D., in 2021 and is backed by marquee venture capitalists including 500 Global. For more information visit:


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