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 big data. The software package enables quickly analyzing disparate data in medical diagnostics and verifying the diagnosis, avoiding errors caused by human factors.
- Early diagnosis detects 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, active work to create new methods to increase the accuracy of diagnosis, speed up the process of information processing, and deliver the finished result is going on around the world.
The information and software system developed by TSU analyzes data of a 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 the patient's blood and a minimum number of simple preparatory procedures.
Also, to solve the problem of early diagnosis, 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, because 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. The software system must handle not only video endoscopy, but also other studies, such as MRT and CT imaging in perspective and analyze them together, capturing suspicious signs that are imperceptible to the human eye.
At TSU, scientists at the research and educational centre Computer Science and Technology, the Faculty of Informatics, and students in the autonomous educational programme the Intellectual Analysis of data and Bioinformatics are taking the most active part in the project.
Along 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).