Mayo Clinic provides HeraMED with a massive dataset of pregnancy records

Medical technology company, HeraMED Limited (ASX:HMD) has received approximately 90,000 pregnancy records from research and development collaborator the Mayo Clinic, which will be implemented into its OrionAI platform.

This provides HeraMED with access to an industry leading digital pregnancy monitoring database, allows for expedited solution development and strengthens OrionAI’s machine learning functionality.

OrionAI is HeraMED’s cloud based machine learning software-as-a-service (SaaS) platform being developed in collaboration with the Mayo Clinic.

OrionAI plans to utilise big data and analyse thousands of pregnancy records in real time to enable potentially unprecedented analysis accuracy.

The platform aims to detect pregnancy complications early, resulting in a possibly significant impact on expecting mothers and unborn children.

Benefits for mothers, medical professionals and hospitals

The solution may also reduce costs for hospitals and clinics, as well as optimising the efficiency of medical professionals.

The data encapsulates over ten years of activity at Mayo and was extracted over several months from the Mayo Clinic’s historical records by its Artificial Intelligence and Machine Learning experts.

Records will be housed on a HIPAA (Health Insurance Portability and Accountability Act) compliant secure server, ensuring the data is well protected and secured.

The records are high-quality and comprehensive and include cardiotocography (CTG) data or birth stage monitors, as well as non-stress test (NST) data, encompassing earlier stages of pregnancy.

This is advantageous to HeraMED, as NST data allows for the development of OrionAI algorithm extensions to also analyse earlier stages of pregnancy.

This also assists HeraMED in incorporating OrionAI with HeraCARE, providing a more homogeneous solution.

Having a large volume of records, which includes the results of the majority of pregnancies will allow OrionAI’s machine learning functionalities to educate the algorithm to gain a better understanding of the correlations between physiological measurements and the effects these have on the pregnancy journey and the health of a baby.

LinkedIn machine learning expert to steer OrionAI

To ramp up development, HeraMED has appointed leading, US-based data scientist, Uri Merhav (M.Sc in Physics, TAU, Magna Cum Lauda) as OrionaAI chief architect.

Mr Merhav was former staff machine learning engineer at LinkedIn and author of seven registered machine learning patents.

He is a machine and deep learning expert and was fundamental in creating HeraMED’s first foetal heart rate algorithm.

Merhav joins HeraMED’s professional innovation team which includes Dr Arturo Weschler MD, Oren Kapach (PhD Computer Science), Roei Tov (PhD Computer Science) and Yael Kierson (M.Sc. Medical Physics).

Commenting on the significance of this development in terms of optimising the group’s database, chief executive and co-founder Mr David Groberman said, “These records provide HeraMED with an unprecedented level of digital pregnancy monitoring database.

‘’This will assist our experts in the efforts of turning OrionAI into the most advanced AI based diagnostic tool for pregnancy wellbeing analysis .

“Uri is considered a prodigy and one of the brightest minds in machine learning, and bringing him to lead the company’s AI initiatives with his unique capabilities and proven knowledge is of great value.

“As additional datasets are planned to be implemented, OrionAI will only become stronger, smarter and more resilient.

‘’We believe It will provide improved pregnancy monitoring solutions for expecting mothers, while also allowing medical professionals to optimise their time and become better patient advocates.

“We look forward to continuing our work with Uri and the Mayo Clinic and providing updates to shareholders as developments progress.”