Singapore approves medical AI software for automated analysis of vascular ultrasound

  • AVA uses deep learning, text recognition, and signal processing technologies
  • Intended to assist the clinician interpreting and reporting vascular ultrasound studies

 

The See-Mode Technologies team

SEE-Mode Technologies, a medtech startup based in Singapore and Australia, on Dec 10 announced regulatory approval for its debut product, an AI-based software for automated analysis and reporting of vascular ultrasound scans, one of the most common scans used for patients with cardiovascular diseases.

See-Mode’s first product, AVA (Augmented Vascular Analysis), has been approved as a Class B medical device by Singapore’s Health Sciences Authority (HSA).

See-Mode’s AVA uses deep learning, text recognition, and signal processing technologies and is intended to be used as an assistant to the clinician interpreting and reporting vascular ultrasound studies, which are commonly reported through a manual, time-consuming, and error-prone process.

To report a vascular ultrasound scan, a clinician, usually a sonographer or radiologist, has to manually review and analyse 50-150 individual images for each patient, consisting of various types of ultrasound images and doppler waveforms.

The end result is a hand-written, paper-based template filled with drawings, numbers, and measurements, which can take as long as 20 minutes per patient for severe cases.

“During our collaboration with different hospitals, we have observed cases where the mistakes in hand-written ultrasound worksheets could potentially result in the wrong treatment plan for a patient, for example, surgery on a wrong vessel.

“Given that these reports are produced by clinicians who acquire and review hundreds of images per day, human error is inevitable. Our intention with AVA is to give an assistive tool to clinicians to improve efficiency and minimise potential errors without making any changes to their established clinical workflow,.” said Dr Sadaf Monajemi, co-founder of See-Mode Technologies.

See-Mode’s AVA utilises multiple deep learning models for image analysis, as well as text recognition and signal processing algorithms, and puts together a computer generated report in less than one minute with a single click.

After this vascular ultrasound report is generated by the software, the control is handed over to the clinician who reviews the report and can make adjustments, before confirming the final report.

With this methodology, See-Mode’s AI is augmenting the clinical workflow, resulting in greater overall productivity, accuracy and improved patient outcomes.

With the HSA approval in hand, See-Mode is now pursuing regulatory approval for AVA in other regions, including TGA, CE and FDA.

Dr Milad Mohammadzadeh, See-Mode’s co-founder, said: “While we work towards getting AVA to a larger user base, we are continuing on our mission of assisting doctors to predict and prevent stroke.

“See-Mode is building machine learning and computational models for extraction of stroke biomarkers from CT and MRI. We are collaborating with some of the most prominent stroke centres in the world to assess these models and bring them into hospitals, aiming to help doctors improve patient outcomes.”

See-Mode announced its seed funding round of US$1 million in early 2019, with participation from SGInnovate and Cocoon Capital in Singapore, and Blackbird Ventures in Australia.

“As people around the world grow older and live longer, there is an increasing need for new healthcare solutions. Globally, rising demands for greater healthcare infrastructure and resourcing are exceeding the ability of public and private systems to meet them.

“At SGInnovate, we firmly believe Artificial Intelligence, as a group of technologies will be vital in helping medical professionals perform their jobs more effectively and efficiently. Receiving this regulatory approval is a significant milestone for See-Mode.

“As one of the earliest investors in See-Mode, we are proud to know doctors and clinicians will be able to improve patient care using the AI systems being built by the team,” said SGInnovate founding chief executive officer Steve Leonard. 

 
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