AI Project With Vietnamese Participant Wins The European Technology Prize
AnalysisMode, a Finnish startup, is one of the most promising startups selected for the Health Incubator Helsinki program starting in spring 2021. AnalysisMode was founded in 2017 with 13 members, including a young Vietnamese girl named Minh Anh Le. She is a daughter of an official currently working at the Voice of Vietnam (VOV).
In 2020, this company won at 5 events of HackTheCrisis and was a finalist at EU vs Virus, which took place from April 24 to 26, 2020 by the European Commission and the Council of European Initiatives. It aimed to build partnerships among investors, innovators and social partners, to find solutions in the areas of health, remote work and learning, as well as social and political cohesion, to ensure smooth digital finance and e-commerce activities. Previously, this company also won the Finnish Ultrahack competition, known as a competition to develop solutions to important social problems.
|AnalysisMode team from left to right: Tiago Sampaio, Mia (Minh Anh) Le, Milda Dapkeviciute and Teppo Hudsson. Photo: Jonas Simberg.|
This year, AnalysisMode has won the EU Data 4 Healthy Recovery hack-athon, an online programming competition that aims to solve the most urgent smart health challenges presented by companies in various industries in Europe. Recently, it was also selected as the winning team at EU Data 4 Healthy Recovery Accelerator.
What is AnalysisMode?
AnalysisMode builds a virtual home lab for scientists to conduct simulation experiments. Artificial Intelligence (AI) software is used for the prediction and development of experiments without requiring any programming skills from the users.
Instead of spending hundreds of hours a year manually analyzing experimental data in laboratories, AnalysisMode provides a software that can ensure accuracy in just a few hours.
The question is how does this software work?
With AnalysisMode, scientists use previous experimental data, usually in the form of spreadsheets, to input into the software. AnalysisMode is able to train data analytics AI to predict and design new experiments.
"With our solution, you can predict experiments even before you create them," said Tiago Sampaio, the co-founder and director of product research and development of the company.
|AI Photo: pioneeringminds.|
Instead of using a real bioreactor, AnalysisMode's virtual bioreactor supports simulations of experiments in different ways from CHO cells, T cells, virus vectors and many other elements can be added according to customer's request.
AnalysisMode software can run tens of thousands of simulations based on input provided by scientists, uncover additional "recipes" for cell culture experiments.
"From simple text data, we can predict features at the molecular level," explains Sampaio.
He also shares that scientists using AnalysisMode's solution can increase detections by five times, as well as save about 250,000 euros in biological research and production costs annually.
"Scientists are using AnalysisMode's solution to be able to increase the detections by 5 times and to save money".
Open the AI "black box"
According to Sampaio, this virtual model has some striking features from a scientific perspective. First, it can work with small amounts of data, which is useful when responding to new pandemics.
|AI Photo: myconstructiontips.|
"Secondly, our AI technology can interpret each prediction in human language instead of a mathematical formula. It's adaptive, which means that you don't need to retrain the entire AI every time new data is added".
Finally, with this model, scientists can understand why AI makes such predictions and research can progress much more smoothly.
"We've turned the AI black box and into an easy-to-understand interface to make this possible," revealed Sampaio.
Revealing the secret of AnalysisMode's success, Sampaio shared: "I believe that the combination of expertise and determination has helped us win these programming competitions. We have put all our efforts and resources into the project”.
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