Early and rapid diagnosis of lung or pancreatic cancer increases the life expectancy of the patients. The use of artificial intelligence as a diagnostic tool in spectrum analysis enables an order of magnitude faster analysis compared to the common diagnoses. With each data collection the neural networks improve, making the analysis more accurate and reliable. A great advantage of the method is the use of the entire spectra of the urine or breath. Contrary, competing methods analyze only individual VOC molecule spectra.
The project "Research of spectroscopic methods for early, non-invasive real-time identification of selected diseases from gas condensate released by the lungs and skin" is co-financed by the European Union.
The aim of the project: The aim of the project is to achieve a significant change in the standard diagnostic procedures used so far for patients with cancer in the Slovak Republic in order to enable fast and accurate differential diagnosis with a clear division of pre-cancerous and cancerous conditions by proposing relevant differences in the spectra of exhaled air through the lungs and skin respectively, and subsequently creating new diagnostic algorithms suitable for a quick and cheap screening of suspicious patients.
| Non-refundable financial contribution: | Receiver: | Receiver's partners: |
| 1 345 250,20 EUR | Univerzita Komenského v Bratislave | HOFITECH s.r.o. |
| Novo s.r.o. |
Information on the Operational Program Integrated Infrastructure 2014-2020 can be found at www.opii.gov.sk.
