Diagnostic Match aims to get the most out of big data

Connected Health member Diagnostic Match successfully applied for the AI4Diag project. The project supports diagnostic companies in exploring the potential of Artificial Intelligence (AI) and machine learning for their business, making them more competitive on a global scale.

AI4Diag is a European cluster project aimed at contributing to disease prevention and disease burden forecasting using AI-based diagnostic technologies.

AI4diag promotes enterprise development, helps attract investment and creates a long-term strategy for collaborative industry modernisation and internationalisation.

According to Grete Kikas (Diagnostic Match), the project caught her eye and after a recommendation from Piret Hirv, head of the cluster, she was inspired to continue.

“The application process was not complicated,” said Kikas. “We set our direction and goals with the team, filled out the application form and the ball started rolling. Practically the next day we received the results of the evaluation, in which we achieved a very good overlap with the overall objectives of the project.”

The purpose of Diagnostic Match is to engage big data professionals and scientists as well as receive some help with marketing: “By the end of the 6-month HIV Indicator Pilot Project,” Kikas explained, “we have quite a good amount of data and want to involve professionals to better analyse and understand it; both those who are engaged in purely statistical analysis and those who are clinically competent to assess the relationships and impact of indicator diseases.”

“At the moment,” she adds, “we have received several cooperation offers from various multinational companies and universities. In the near future, we plan to meet with the representatives of the companies and find a suitable partner for Diagnostic Match to meet the objectives of the project.”

AI4Diag is funded by the COSME Programme of the European Union for the Competitiveness of Enterprises and Small and Medium-Sized Enterprises (SMEs).