+380442049064
Data processing and analysis, machine learning
▶ Python for Data Science, AI & Development
▶ Machine Learning Specialization
The innovAID - inspired project
Welcome to the innovAId: a project devoted to advancement of the AI-empowered innovations in digital healthtech. This website is aimed at supporting the process of development of innovative solutions to improve the patients treatment.
This website serves as a digital testbed entry point which guides innovation ideas from staff and students through the different phases of the innovation funnel.
Here you can find a collection of educational materials to learn how to develop and deploy AI models, a library of databases with medical data for machine learning. Also, we have an innovation partner Innovation Ecosystem "Sikorsky Challenge Ukraine" which supports you in establishing the startup project.
Our collaborators and partners are ready to work together on the implementation of AI solutions for healthcare, from domain expertise in consulting to clinical evaluation support.
Here you can find a collection of educational resources, useful for mastering the implementation and application of AI and machine learning for healthtech.
▶ Python for Data Science, AI & Development
▶ Machine Learning Specialization
▶ Azure Solutions for the healthcare industry
▶ Tutorial: Deploy and review the continuous patient monitoring application template
▶ FHIR Specification (v5.0.0: R5 - STU)
▶ CRISP-DM standard for machine learning projects development
For biomedical research, medicine, and healthcare there are a couple of outstanding academic databases that provide true value in your daily research.
▶ Here you can find an alphabetical list of all the databases on PhysioNet.
▶ To search content on PhysioNet use search page.
We have a list of partner institutions ready to collaborate on development of AI tools for healthcare. If you are interested in being listed as a partner, or need support for your research - please contact us.
If you already have an idea in the field of AI in digital healthtech and want to turn it into your own business but need help knowing where to start, we will help you bring your dream to life.
The Digital Health Testbed closely collaborates with the All-Ukrainian Innovation Ecosystem "Sikorsky Challenge Ukraine" (SCU).
SCU is an open innovation ecosystem that unites institutions interested in developing the Ukrainian innovation economy: universities, research institutions, state authorities, local authorities, business companies, funds and NGOs, international representations, and foreign partner organizations.
The free Startup School Sikorsky Challenge operates based on the Ecosystem.
The Startup School is the first step of knowledge and skills, providing an environment where creative individuals receive not only theoretical knowledge and practical skills in the creation of innovative technology startups but also the conditions for implementing their ideas into a functional business.
The Startup School operates throughout the year. To register for the training, you must fill out an application form on the website. After that, the managers of the Startup School will contact you and provide information about the start date of the training.
The preparation based on SCU methodologies consists of 4 stages.
Stage 1. Training:
Stage 2. Incubation:
Stage 3. Participation of selected teams in local startup competitions:
Stage 4. Acceleration of startup projects according to the needs of investors:
However, the work doesn't end there. Successful startup projects enter the portfolio of the ecosystem, where interested investors can continue to learn about the teams and invite them for pitching, investing and further collaboration. The ecosystem mentors provide guidance and support at every stage of your business's development and implementation. This makes your business competitive, successful, and capable of easily overcoming market entry barriers and scaling up.
Let's turn an idea into a real business together!
EOGView is a technology-based project focused on developing an eye tracking system using Electrooculography (EOG). EOG signals are generated by the movement of the eyes, and EOGView aims to capture and analyze these signals to accurately track eye movements.
The innovation in EOGView lies in its approach to eye tracking using EOG signals. By focusing on EOG, the project aims to provide a non-intrusive, cost-effective, less resource-intensive, secure, and versatile solution for eye tracking and health tracking.
NanoSpace is advancing a unique technology that merges molecularly imprinted polymers and aptamers with Carbon nanotube sensors, and a microfluidic platform for rapid, accurate virome detection.
Simultaneously, we're developing artificial intelligence software to analyze the virome data, aiming to predict potential gut diseases. This approach is set to redefine the landscape of medical diagnostics and prevention.
biomedical signal analysis, computer vision, machine learning, deep learning
biomedical signal analysis, biomedical signal processing, machine learning
biomedical signals acquisition, system design, biomedical signal analysis, patient monitoring, distributed systems, embedded systems
biomedical signal analysis, machine learning
accelerating and mentoring early-stage startups, ideas to market, project management, validation process, business plans, building marketing strategies
design of a mechanical system, dynamics of movement and strength of bodies, natural frequencies and modes of oscillations
If you need any support or consultancy on the AI application in digital healthtech, please contact us
+380442049064
popov-ee@lll.kpi.ua
Polytechnichna St, 16, Bld.12, of. 423, Kyiv, Ukraine