In the last few years, Artificial Intelligence and data management have emerged as very powerful tools in reshaping the healthcare landscape. The seamless integration of AI algorithms and comprehensive data management systems has the potential to revolutionize patient care, improve diagnostic accuracy, and optimize resource allocation.
However, it is imperative for healthcare organizations to navigate the ethical and security challenges associated with handling sensitive patient data.
By harnessing the transformative potential of AI and data management, the healthcare industry can unlock a future where personalized, efficient, and proactive care becomes the new norm.
The role of AI and Data Management in Healthcare: ongoing research in medical, life science and diagnostic fields
Since the very beginning of this revolution, Datrix Group and its companies have engaged in many different projects of considerable social utility, in particular in various EU funded Research and Development Projects dedicated to Healthcare and Biomedical innovation.
In the Life Science & Healthcare sector, the Group is developing AI models for 3 main projects:
- CONcISE, promoted by Horizon Europe, which started in February 2023, with the aim of bringing to market more data-efficient, quality-driven techniques for biomedical optical imaging in biological tissues. The aim is to develop low-cost, non-invasive pre-screening solutions, with high reliability and precision, to be used for the diagnosis of breast and thyroid tumors and for the detection of ischemia;
- Organ Vision, based on real-time visualization and modeling of fundamental processes in living organs, it aims to enable new insights into organ-specific health, disease and recovery;
- CRIMSON intends to develop a new methodology that applies coherent RAMAN spectroscopy (CRS), a technology based on the vibration of molecules. Combined with AI, this method will facilitate the classification of cells and tissues with unprecedented biochemical sensitivity, paving the way for the design of personalized treatments.
Furthermore, collaborations with research and academic centers and hospitals frame the avant-garde scenario in which Datrix promotes technological innovation and a data-driven approach to better settle two crucial scenarios: the medical evolution and Cybersecurity.
The aim is to develop innovative approaches to securely exchange and reuse patient’s health data in a EU compliant fashion, within the European Health Data Space, a trustworthy ecosystem of rules and practices for secure access to and processing of a wide range of healthcare data.
The partners: Datrix, UKK and IMGGE
Datrix is in fact the technological partner for the Personal Health Train Project, a distributed analytics paradigm developed in collaboration with the Institute for Biomedical Informatics of the University Hospital Cologne (UKK) and the Institute of Molecular Genetics and Genetic Engineering (IMGGE), University of Belgrade. IMGGE is a Western Balkans leading institute when it comes to genomic research and diagnostics of pediatric rare diseases.
The collaborative effort of Datrix in developing innovative AI tools will increase IMGGE’s capacities for genomic research and will further contribute to reducing time to diagnosis and enabling the development of the most promising strategies for new rare disease therapeutics.
An Innovative Framework
The operational framework is intended to offer a new paradigm and a fresh approach for achieving a twofold aim: an easier and faster access to functionality offered in closed, siloed systems residing in hospitals and medical and clinical research settings, while also meeting the need for lower, affordable and rationalized costs for integration and achieving reduced error-prone operation.
In order to enable health data sharing across national borders, fully comply with present GDPR privacy guidelines and innovate by pushing research beyond the state of the art, the proposed framework proposes a robust decentralized infrastructure which will empower researchers, innovators and healthcare professionals to exploit the full potential of larger sets of multi-source health data via tailored made AI tools. These will be useful to compare, integrate, and analyze in a secure, cost-effective fashion, with the very final aim of supporting improvement of citizen’s health outcomes.