Hillel's Tech Corner: MDGo: Car accidents are no match for AI and ML

MDGo's latest innovation is proving to be a big help in every way from medical imaging, to drug discovery, to medication management, and even robotic surgery.

AUGUST 23, 2019 01:33

There are not many things more traumatic than a car accident, especially a serious one. The medical treatment following the accident very much depends on an initial on-the-spot diagnosis, mostly based on the pain you may be feeling at that moment. In other words, misdiagnosis after a car accident is something that is extremely common and incredibly dangerous.

According to the European Commission of Mobility and Transport, 44% of fatalities resulting from car crashes could have been avoided if real-time information about the type and severity of their injuries existed. Somehow, that information has never become available. A majority of car crash fatalities do not occur at the scene, but only in the hours and days that follow. As a result, 32% of deaths are caused by evacuations to the wrong hospital, and an additional 12% as a result of a complete lack of information regarding the passenger’s status.

The direct result is a delay of treatment, and in some cases mistreatment. This has both a medical and economic impact. For example, on the economic side, a person with secondary brain injury (one of the leading causes of death in car crashes) who’s been evacuated to a level 1 trauma center within one or two hours of the crash, is likely to be released home after three to five days with no long-lasting damage. That person can then claim an average of $50K from insurance.

However, if the same person is evacuated to the wrong hospital, and then to a level 1 trauma center after four hours, the individual is likely to suffer long-term cognitive damage and can claim close to a million dollars from insurance. After six hours, a vegetative mode is likely to develop, reaching $4 million in insurance claims.

There has to be a better way than asking the person “What hurts?”

Well, as you probably noticed, you can’t talk about modern technology today without mentioning the terms artificial intelligence (AI) and machine learning (ML). Now imagine using AI and ML combined with the car’s already built-in sensors, and what you have is a more effective way to diagnose and treat patients after a car accident. What you have is MDGo.

We’ve already heard of companies in the healthcare industry turning to AI and ML to mine medical records in an effort to provide better and faster health services. It is proving to be a big help in every way from medical imaging, to drug discovery, to medication management, and even robotic surgery.

When it comes to the application of AI and ML technologies in the automotive industry, most people associate it with the quest of auto and tech giants for fully autonomous vehicles, but there’s so much more to it than that. I’m talking about features such as driver assist, predictive maintenance, driver identification and recognition, and risk assessment.

THEN THERE is MDGo. The team uses AI and ML technologies to build a bridge between the automotive and healthcare industries. MDGo has developed a real-time accident analysis technology that relies only on existing vehicle sensors or telematics solutions. The company’s technology generates a comprehensive report regarding the vehicle damage and the type and severity of the passenger’s injuries by body region. Then it delivers that information automatically to the first responders and relevant hospitals.

The system can save lives, decrease long-term morbidity, save rehabilitation expenses and reduce the amount and size of liability claims, without installing any extra hardware in the vehicle. MDGo does this by making use of existing sensors and infrastructure in connected vehicles in order to generate new insights and value from the medical point of view. This a very important point. No extra devices have to be installed in the car.

MDGo was founded in January 2018 by Dr. Itay Bengad, CEO; Eli Zerah, VP R&D; and Gilad Avrashi, CTO. The company has

raised $8m.

There are four steps to how the system works. First, the system reconstructs the accident scenario, including accident mechanism, velocity and angle of impact. Then it measures the physical forces acting on occupants during the car accident, leveraging existing vehicle sensors. MDGo then translates this data into medical insights using AI and biomechanical tools, and finally, it delivers this analyzed data to first responders and hospitals. That process takes about six seconds and is fully automatic.

In case the ramifications of MDGo aren’t clear, there are numerous benefits that MDGo provides to society as a whole. First and foremost is the high potential decrease in road fatalities. It also helps save time, money and resources when you factor in the potential loss in productivity, medical costs, legal costs, emergency service costs, insurance administration costs, and more.

When you look at leading companies in the technology sector, you might notice a common thread. They are all addressing old industries, things all of us do and need, then using technology to disrupt it and increase efficiency. MDGo is no different. Car accidents happen, and they happen often. In most cases, real-time data about injuries can save a person’s life. Using MDGo’s technology, car manufacturers can significantly increase the safety of their cars and save the lives of their customers when it is needed most.