TSU and Arizona State University are beginning a joint project for the early diagnosis of diseases, including cancer, using the methods of pattern recognition and intelligent analysis of large data. The software package allows to quickly analyzing disparate data in medical diagnostics and verifying the diagnosis, avoiding errors caused by human factors.
- Early diagnosis allows to detect the disease before the critical moment, thereby increasing the patient's chances for recovery and reducing the duration of treatment, - says Alexander Zamyatin, head of the Department of Theoretical Foundations of Computer Science, director of the TSU Centre of Computer Science and Technologies. - Therefore, the active work on the creation of new methods increasing the accuracy of diagnosis, speeding up the process of information processing and delivering the finished result is going around the world.
The information and software system developed by TSU provides an analysis data of different nature - static and dynamic. A new promising method for highly sensitive analysis of the immune signatures was provided as a source of static data. It is based on the use of peptide microarrays for detection of specific antibodies produced against antigens that emit the tumor cells. Using this method requires a small amount of a patient's blood and a minimum number of simple preparatory procedures.
Also, in the solution of the early diagnosis problem it is proposed to analyze the dynamic information, in this case, the video results, obtained using the endoscopic method of diagnosis - colonoscopy. Today, the analysis of these data is performed by diagnosticians with high qualifications.
- All these data are characterized by their features and large volume. There is a need for intellectual analysis of the data processing and interpretation, it is the tool that will not only speed up the process of reading the information supplied by the body of the sick person, but it will make this reading correct, - says Alexander Zamyatin. We are striving to ensure that our method will be invariant. In the perspective the software system must handle not only video endoscopy, but also other studies, such as MRT, CT imaging and analyze them together, capturing suspicious signs, imperceptible to the human eye.
At TSU, scientists of the research and educational centre Computer Science and Technology, the Faculty of Informatics, and students of the autonomous educational programme the Intellectual Analysis of data and Bioinformatics are taking the most active part in the project.
Together with Arizona State University - the key partner of TSU, this project involves partners from Altai State University (Russian-American Anti-Cancer Center), the Technical University of Dresden, Goldsmiths, University of London, and Pirogov Russian National Research Medical University(RNRMU).