LLC "FtizisBioMed" (FBM), established in 2015 as a subsidiary of the Federal Telecom Operator JSC "Vector Radio Company", specializes in the development, operation and integration of intelligent services for healthcare and telemedicine, as well as training medical and technical personnel to use artificial intelligence products.

FtizisBioMed products and services are used in practical medicine in medical decision support systems to reduce the number of erroneous diagnoses and diagnoses in the early stages of the disease.

The results of the application of FtizisBioMed products and services are also used by health authorities to improve the manageability of health systems at different levels.

Together, these results allow an increase in the number of patients undergoing successful treatment while optimizing treatment costs. Application of FtizisBioMed products and services accelerates the transition to digital healthcare of the modern world level.

The most famous and most important at the moment development of the FBM is the "cloud service" FtizisBioMed for the analysis of medical images (digital fluorograms and chest radiographs), created on the basis of artificial intelligence (AI), which is an ensemble of convolutional neural networks.

An important advantage of the FBM AI service in relation to other similar developments is the multi-step technology of creating and constantly replenishing its own dataset for machine learning. At the moment, the dataset contains more than 240,000 original digital X-ray and fluorographic images obtained and marked up by leading specialists of Federal Medical Centers in Russia and from open foreign dataset banks. Outstanding radiologists and pulmonologists led by Academician Alexander Grigoryevich Chuchalin, former chief freelance pulmonologist of the Ministry of Health and Irina Anatolyevna Vasilyeva, director of the Federal State Budgetary Institution "National Medical Research Center of Phthisiopulmonology and Infectious Diseases" of the Ministry of Health of Russia, as well as professional mathematicians and programmers, graduates and employees of the Moscow Institute of Physics and Technology participated in the creation of the AI service and dataset. – National Research University. For users wishing to get acquainted with the work of the service, a demo version is available on the Internet at ftizisbiomed.ru.

At the moment, the functionality of the service allows you to detect suspected pathologies, make their graphical localization on the analyzed images, and also classify the detected pathological area.

The pathology classifier of the FtizisBioMed service is able to distinguish and catalog 9 types of pathologies (Pleural effusion, Pneumothorax, Atelectasis, Nodule, Infiltration / consolidation, Multiple nodules, Cavity, Calcinate / calcified shadow, Rib fracture).

In addition, the service gives a numerical value for the probability of the presence of pathology. The localization areas are marked with the help of contours, the color schemes of which correspond to the probable classes of pathological signs given in the caption to the image processed by the AI service.

From 2018 to the present, the FtizisBioMed service has passed several independent tests, including the service was tested at the site of the State Budgetary Healthcare Institution "Scientific and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Department of Healthcare" («Moscow Radiology»).

НScientific articles on assessing the accuracy and effectiveness of the proposed service have been published in peer-reviewed journals indexed by Scopus and / or Web of Science:

- С. П. Морозов, А. В. Владзимирский, Н. В. Ледихова, И. А. Соколина, Н. С. Кульберг, В. А. Гомболевский «Оценка диагностической точности системы скрининга туберкулеза легких на основе искусственного интеллекта» Туберкулёз и болезни лёгких, Том 96, № 8, 2018

- V.I.Klassen, A.A.Safin, A.V.Maltsev, N.G.Andrianov, S.P. Morozov, A.V.Vladzymyrskyy, N.V.Ledikhova, I.A Sokolina, N.S.Kulberg, V.A Gombolevsky, E.S.Kuzmina «AI-based screening of pulmonary tuberculosis: diagnostic accuracy» Journal of eHealth. Technology and Application, Volume 16, Number 1, November 2018, ISSN: 1881-4581

To create a modern system for combating the epidemics of tuberculosis and COVID-19, the Russian government organized an Experiment on the use of innovative computer vision technologies for medical image analysis and subsequent applicability in the healthcare system of Moscow.

The FtizisBioMed service participates in the Experiment and, based on the results of 2020 and 2021, is recognized as the leader among other AI services for the processing of fluorograms.

According to the results of the official calibration testing of the latest version of the FtizisBioMed service by the Moscow Department of Health (Protocol of calibration testing of the AI service No. 13 dated 24.03.2021), the following results were achieved: area under the characteristic curve (AUC = 0.95), sensitivity 92%, specificity 92 %. Thus, the total number of errors (including false positive and false negative) is no more than 8%.

Since 2019, the FtizisBioMed cloud service, with the support of the Administrations of 53 regions of the Russian Federation, has been used by doctors of X-ray departments of medical institutions of all levels.

In the process of developing the service, registration documents were obtained that establish intellectual property rights:

1. Свидетельство о государственной регистрации программы для ЭВМ 2017615663 «Программа автоматизированного анализа флюорографических изображений»,

2. Свидетельство о государственной регистрации программы для ЭВМ 2018615227 «Программа для ручной разметки патологий на флюорографических снимках»,

3. Свидетельство о государственной регистрации программы для ЭВМ 2018615226 «Программа автоматизированного анализа флюорографических изображений (версия 2)»,

4. Патент на изобретение 2684181 «Способ автоматизированного анализа ЦИФРОВЫХ флюорографических снимков»,

5. Свидетельство о государственной регистрации базы данных 2020620858 «Размеченные результаты флюорографии».

June 21, 2021 FtizisBioMed LLC became the winner of the National Award in the field of entrepreneurial activity "Golden Mercury", established by the Chamber of Commerce and Industry of the Russian Federation, in the category "Innovative Activity".

On October 6, 2021, FtizisBioMed LLC became the winner of the IT Stars 2021 award named after George Gens in the nomination "Innovative project in Healthcare".

On November 16, 2019, FtizisBioMed LLC filed an application for registration of the "Program for automated analysis of digital chest X-rays/fluorograms" as a medical device.

The FBM service was the first to undergo a clinical trial process using the unique methodology of the NPCC DiT DZM. The certificate of evaluation of the results of clinical trials 001 was received on 27.10.2021.

Due to the change in the legislation on registration of medical devices (MI) from 1.01.2022, the registration of MI was somewhat slowed down due to the large number of applications under the old legislation. Nevertheless, LLC "FtizisBioMed" received an official decision to assign the status of a medical device to the FBM service on 31.05.2022 under the number RZN 2022/17406.

Purpose of using the service

The software product automatically evaluates the probability of pathologies on radiographs and a fluorogram of the chest organs. Searches for and localizes pathological signs. It is used in the medical decision support system.

The license rights belong to "FtizisBioMed" LLC

Work principles

Clinical problem to be solved: Identification of signs and cataloging of pathologies of the chest organs

Instructions for using the cloud service.

Instructions for using the FtizisBioMed cloud service are available at: https://ftizisbiomed.ru/.

To access the full functionality of the service, it is necessary to conclude an agreement for the use of the software product with FtizisBioMed LLC. Within the framework of the agreement, the User also has the opportunity to conclude additional agreements with FtizisBioMed LLC regarding training medical personnel to use the service and / or organizing telemedicine consultations with leading specialists of Russian Federal medical centers.

Output data:

• probability of the presence of pathological signs of chest organs;

• localization of pathological signs of chest organs.

Target population:

Adult patients over 18 years of age

Input data type:

digital medical image in DICOM, JPEG, PNG formats

Service Neural Network model type:

U-Net

Validation and performance:

Area under the ROC-curve (AUC) - 0,96

Sensitivity - 94%

Specificity - 93%

Accuracy - 94%

Analysis duration of 1 study - 1 s

External validation:

Area under the ROC-curve (AUC) - 0,965

Sensitivity - 92%

Specificity - 94%

Accuracy - 93%

Analysis duration of 1 study - 10 s

Purpose and instructions for use

Target population and area of use: Adults (over 18 years of age) undergoing routine fluorographic screening, as well as having a referral from a doctor for a chest x-ray for suspected disease, or monitoring the effectiveness of treatment for changes in the lungs. AI-service "FtizisBioMed" specializes in the automatic analysis of images of chest x-rays (fluorograms) in order to identify and localize pathological changes in the lungs.

Purpose of the Software Product: Analysis of digital radiographic images of the chest organs and identification of signs of pathologies of the chest organs.

The service is a support system for making medical decisions.

Limitations on the use of the Service:

Demographic:

- Children's age (under 18 years old);

Personal:

- Non-anonymized data (the presence of the patient's full name);

- Artifacts from foreign objects at the research level, which are superimposed on the lung area;

- The position of the patient's body, which differs from the position regulated for obtaining a direct projection;

- Research performed in any phase of the respiratory cycle, except for holding the breath at the depth of inspiration;

Technical:

- Study modality, different from radiography / fluorography;

- Anatomical area of study, which differs from the chest organs in full (from the tops of the lungs to the pulmonary sinuses);

- Projection of the study, different from the antero-posterior or postero-anterior;

- Data outside DICOM 3.0 format or images outside of JPEG, PNG, DCM formats.