The first working prototype of the platform is hosted on the popular GitHub service, and developers from all over the world can take part in its improvement by adding verification criteria depending on the purpose of the services.
Center for Diagnostics and Telemedicine
Experts from the Center for Diagnostics and Telemedicine have developed a platform for self-testing services which is based on artificial intelligence and designed for medical tasks, such as for analyzing diagnostic images. The first working prototype of the platform is hosted on the popular GitHub service, and developers from all over the world can take part in its improvement by adding verification criteria depending on the purpose of the services. Sergey Morozov, CEO of the Center for Diagnostics and Telemedicine, spoke about this at the thematic week dedicated to artificial intelligence which was part of the program of the European Congress of Radiology (ECR 2020).
Before implementing a service based on artificial intelligence (AI) into routine clinical practice, it is necessary to test it for technical readiness, as well as to verify whether it meets the stated characteristics. It is called analytical validation of the algorithm. The services that have passed it are allowed to be integrated into medical systems, including city healthcare.
Integration is a complex and expensive process, so it becomes a barrier for many teams that cannot guarantee the required accuracy and speed of the algorithm processing data of the system into which they are integrated. Currently analytical validation is performed manually. Manual validation allows accidental or deliberate deviations from the approved test program, as well as manipulation of datasets, and also can potentially put different test participants in unequal conditions.
To solve these problems and automate the verification process, ensuring trust of users, specialists of the Center for Diagnostic and Telemedicine have developed a platform that allows developers of AI-based services to independently conduct preliminary tests (analytical validation) of their algorithms. A prototype of the platform has been hosted on the GitHub, and the first version of the service for exchanging datasets and data analysis results has already been uploaded.
The platform provides an opportunity for the unlimited number of accesses to single samples of data instances from the test set in order to fine-tune algorithms. It has uniform rules of use, and it is possible to test several services simultaneously. At the same time, the platform records the time that the software spends on data processing (time-study), and the developers receive an automatic report on the results of testing, – explains Sergey Morozov, CEO of the Center for Diagnostic and Telemedicine.
By automating the entire process on the self-testing platform, the human factor is minimized, which makes data manipulation (to improve results) impossible. In addition, the comparison of the service’s verification results with the reference data is absolutely transparent – the developer can see what metrics were used, and how the final result reflected in the report was calculated.
Anyone can take part in improving the platform and add necessary metrics to it, which will be used to evaluate the algorithm’s performance for certain medical purposes (for example, for analyzing radiographs or mammograms). However, the addition of the platform will be monitored – the only metrics that have scientific justification will be included in the platform operating on the basis of the Center, – notes Nikolai Pavlov, the developer of the platform, Head of Dataset Labeling Conveyor of the Medical Informatics, Radiomics and Radiogenomics Sector, Center for Diagnostics and Telemedicine.
The creators of the platform invite developers of AI algorithms, programmers and researchers to take part in updating and improving the platform in order to develop a uniform, universal, and user-friendly tool for self-testing of artificial intelligence algorithms intended for medical purposes in the international community. At the moment, there is no such tool aimed specifically at the clinical implementation of services based on AI technologies.
The Latest Updates from Bing News & Google News
Go deeper with Bing News on:
AI medical services
- IQ-AI's medical imaging T1+C software granted a US patenton June 11, 2021 at 2:34 am
IQ-AI Ltd said on Friday that the T1+C software, developed by its subsidiary, Wisconsin-based Imaging Biometrics LLC, was granted a patent by the US Patent & Trademark Office. The Jersey-based medical ...
- IQ-AI Shares Jump on US Patent Awardon June 11, 2021 at 1:24 am
By Adria Calatayud Shares in IQ-AI Ltd. rose Friday after the company said that its T1+C software application for medical-imaging procedures was awarded ...
- IQ-AI secures patent for Gad-Free medical imaging softwareon June 10, 2021 at 11:26 pm
The company said the technology eliminates the need to intravenously inject contrast agent during medical imaging procedures and underscores ...
- What 400 Flawed Healthcare AI Models Can Teach Uson June 10, 2021 at 1:23 pm
The hundreds of flaws in AI models built to help tackle COVID-19 could be viewed merely as a consequence of fast-moving efforts to stop a crisis. Yet, academics calling out these flaws want you to ...
- QPharma Launches Neolytica, an AI Focused Healthcare Analytics Firmon June 9, 2021 at 3:45 pm
QPharma, a leader in Medical, Commercial and Compliance Services for the life sciences industry is proud to announce the launch of Neolytica, a subsid ...
Go deeper with Google Headlines on:
AI medical services
Go deeper with Bing News on:
Self-testing of artificial intelligence algorithms
- Artificial Intelligence (AI) Enabled Medical Imaging Market Size, 2025|Top Companies, Trends and Future Prospects Details for Business Developmenton June 11, 2021 at 1:17 am
Enabled Medical Imaging market is a comprehensive evaluation of the market. It does so via in-depth qualitative insights, historical data, and verifiable projections about Artificial Intelligence (AI) ...
- Industrial Artificial Intelligence Market Report 2021 Growth Factors, Product Type, Manufacturers, Application, End User and Regions 2027on June 10, 2021 at 6:32 am
Jun 10, 2021 (The Expresswire) -- "Final Report will add the analysis of the impact of COVID-19 on this industry" “Industrial Artificial Intelligence ...
- Mayo Clinic Partnership Will Accelerate Artificial Intelligenceon June 9, 2021 at 6:30 am
Mayo Clinic and Visage Imaging signed a multi-year collaboration agreement to research and develop artificial intelligence in healthcare.
- Scientists develop artificial intelligence algorithm to enhance efficacy of sleep disorder treatmentson June 8, 2021 at 9:31 pm
In a new study, researchers from the University of Copenhagen's Department of Computer Science have collaborated with the Danish Center for ...
- Artificial intelligence enhances efficacy of sleep disorder treatmentson June 8, 2021 at 5:54 pm
An algorithm based on 20,000 nights of sleep that can improve the diagnosis, treatment and our overall understanding of sleep disorders has been developed.