Summary
- Profile Type
- Research & Development Request
- POD Reference
- RDRPT20240227030
- Term of Validity
- 27 February 2024 - 26 February 2025
- Company's Country
- Portugal
- Type of partnership
- Research and development cooperation agreement
- Targeted Countries
- All countries
Contact the EEN partner nearest to you for more information.
Find my local partner
General information
- Short Summary
- The Portuguese entity is open to integrate a consortium as a partner in computational tasks, namely in the design of Artificial Intelligence / Machine Learning tools for development of new medical AI-powered solutions to support decision-making processes.
- Full Description
-
The healthcare industry is undergoing a significant increase in demands. The pandemic, population growth and chronic illnesses are just some of the key-factors that have been contributing for that increase. To tackle these growing needs, medical digital technologies and, in particular, Artificial Intelligence (AI) powered solutions play an important role in enhancing the diagnostic quality and effectiveness of further treatments, improving the overall efficiency of the already overloaded healthcare world system.
Our team belongs to a renewed Portuguese institution and is seeking participation in a consortium for the DIGITAL-2024-CLOUD-DATA-06-HEALTHCARE-AI initiative. When it comes to AI, we are ready to develop customized algorithms for the project needs. Our capabilities extend to the acquisition and pre-processing of video signals from medical equipment, which allow us its easy integration into AI classification and prediction models. Our relevant work with the processing of medical imaging allow us to deeply understand the mechanics of several techniques and their use to enhance the final quality of our work. We work in the development of Machine Learning models to predict diseases, which helps the improvement of current treatments, by using techniques of supervised and/or unsupervised learning, such as deep learning, convolutional neural networks (CNN), long short-term memory networks (LSTMs), and many traditional techniques from the area.
Our projects are co-developed with clinicians, who strongly present their perspective about the algorithms and its relevance for daily work at a healthcare institute. By harnessing our expertise in AI and healthcare technologies, we are poised to play a role in a consortium, fostering equitable access to advanced healthcare solutions.
Furthermore, our interdisciplinary approach fosters innovation by integrating insights from diverse fields such as medicine, engineering, and data science. Through collaborative efforts, we leverage the collective expertise of our team members to address complex healthcare challenges effectively. By fostering a culture of collaboration and knowledge exchange, we remain at the forefront of cutting-edge developments in AI-driven healthcare solutions.
In addition to our technical capabilities, our institution is committed to ethical AI development and deployment. We prioritize transparency, fairness, and accountability in all stages of algorithm development and implementation. By adhering to best practices and ethical guidelines, we ensure that our AI-powered solutions uphold patient privacy, mitigate biases, and prioritize patient well-being. Our dedication to responsible AI aligns with the consortium's objectives of delivering impactful, trustworthy healthcare innovations to communities worldwide. - Advantages and Innovations
-
We work in the development of Machine Learning models to predict diseases, which helps the improvement of current treatments, by using techniques of supervised and/or unsupervised learning, such as deep learning, convolutional neural networks (CNN), long short-term memory networks (LSTMs), and many traditional techniques from the area.
We apply these tools mainly in image processing and segmentation protocols for any sort of disease. - Sustainable Development Goals
- Goal 3: Good Health and Well-being
Partner Sought
- Expected Role of a Partner
-
The institute is looking for a consortium or groups of partners that misses an entity that can perform the design of Machine Learning models, as that is the type of work-package in which we can collaborate with you. You can either be from industry, R&D from medicine areas, hospitals and other clinical partners, among many others. We are open and able to discuss collaborations.
We are also available to help the coordination in the writing of a proposal to this call, from excellence and impact to final WP architecture. - Type and Size of Partner
- R&D Institution
- University
- SME <=10
- Big company
- SME 11-49
- SME 50 - 249
- Other
- Type of partnership
- Research and development cooperation agreement
Call details
- Framework program
- Horizon Europe
- Call title and identifier
-
DIGITAL-2024-CLOUD-DATA-06-HEALTHCARE-AI
- Submission and evaluation scheme
-
Single Stage Scheme
Opening: 29 February 2024
Deadline: 29 May 2024 - Coordinator required
-
Yes
- Deadline for EoI
- Deadline of the call
- Horizon Europe
Opening: 29 February 2024
Deadline: 29 May 2024
Dissemination
- Technology keywords
- 06001012 - Medical Research
- 06001013 - Medical Technology / Biomedical Engineering
- 06005002 - Sensors & Wireless products
- Market keywords
- 05005022 - Other clinical medicine
- 05006 - Anatomy, Pathology, Immunology, Physiology
- 05002005 - Other medical imaging
- 05001001 - Diagnostic services
- Targeted countries
- All countries