Israeli AI medical imaging firm Aidoc closes series B funding

18 April 2019 (Last Updated December 23rd, 2019 10:23)

Aidoc has raised $27m in a series B funding round led by Square Peg Capital.

Israeli AI medical imaging firm Aidoc closes series B funding
Aidoc’s AI technology is designed to help radiologists expedite patient treatment and improve quality of care. Credit: Gerd Altmann from Pixabay.

Aidoc has raised $27m in a series B funding round led by Square Peg Capital.

This latest round brings the company’s total financing to $40m. Aidoc intends to use the funds to support its technology and marketing team.

Aidoc provides an artificial intelligence (AI) based radiology solution, which is currently available at 100 centres. The company plans to extend its footprint to 500 hospitals over the next two years.

Approved by regulatory agencies in the US and Europe, the technology is designed to flag acute anomalies in medical scans. It will help radiologists expedite patient treatment and improve quality of care.

“Providing public visibility on the real-life clinical impact of AI across diverse settings is crucial for the continued adoption of these technologies in medical practice.”

Aidoc said that deep learning technology continuously runs in the background and allows better focus on diagnosis. It flags the most serious cases that require quicker diagnosis and treatment.

Aidoc co-founder and CEO Elad Walach said: “We’re working with the American College of Radiology Data Science Institute (DSI) to continuously monitor the performance of our solutions that are already active within hospitals across the US.

“Providing public visibility on the real-life clinical impact of AI across diverse settings is crucial for the continued adoption of these technologies in medical practice.”

Aidoc is planning to launch a range of oncology solutions and expand its existing line of time-sensitive conditions to X-ray. This announcement follows a recent report highlighting the growing importance of AI in diagnostic medical imaging.

Published in the Radiology journal, the report is based on a workshop co-sponsored by the National Institutes of Health (NIH), the Radiological Society of North America (RSNA), the American College of Radiology (ACR) and The Academy for Radiology and Biomedical Imaging Research (The Academy).

Though machine learning research is still in its early stages, the organisers believe that AI algorithms would transform clinical imaging practice over the next ten years.