Periodic Reporting for period 2 - HEARTBIT_4.0 (HeartBIT_4.0 - Application of innovative Medical Data Science technologies for heart diseases.)
Okres sprawozdawczy: 2021-04-01 do 2022-12-31
Data science is not a technology of the future; it is happening here and now, also within the healthcare sector, offering a number of benefits, such as an improvement of a diagnosis process (eg. its time and accuracy). The leader of the project, Wroclaw Medical University (WMU), is one of the biggest centres of medical education, clinical and scientific research in the south-west of Poland while the Institute of Heart Diseases at WMU, has an extensive experience in designing and conducting research projects and multinational studies, mainly in the field of cardiology, confirmed by multiple publications in prestigious journals. However, before the HeartBIT_4.0 project, both the Institute as well as the whole WMU had never been involved in any project and had no experience in relation to data science / medical data science. Thus, our aim was to upgrade the research profile of the leading institution by supporting its staff in the development of new competences via significant knowledge transfer based on the series of educational activities with the help of our partners, real experts in the field of data science.
Nowadays data science is a strategic element in the development of health care system. Hence, it is essential for medical staff to realize where data science may affect their work since there is a constant growth in the number of such areas and their scope is increasing. Staff without such awareness will not be able to benefit from the development of medical sciences combined with the potential offered by data science which may lead to better diagnostics, fewer medical errors, acceleration of many processes, optimization of staff workload and much more. This process that has already begun, is accelerating every day and can be neither avoided nor ignored. What is more, the lack of staff awareness in the field of data science in medicine may badly affect patients and, as a result, a large part of society.
The primary objective was to establish the Centre of Excellence in Medical Data Science (CEMEDS) at WMU, defined as the team of competent scientists with new research excellence who are familiar with innovative technology and clinical study development at the state-of-the-art level in the fields of medical Big Data, modern biostatistics and clinical database technologies. The secondary objective was to complete the networking gaps between the medical field and institutions with experience in the area of Big Data, Machine Learning, database technologies, information engineering and technology, e-health, medical informatics, mathematics and advanced modern statistics. Our success in this context was based on the series of national and international activities and achievements. Additionally, HeartBIT_4.0 was our first project funded by the European Union, where WMU acted as the leader of an international consortium. With the help of our excellent partners who gave us constant support by sharing their experience, we succeeded in increasing the competence of WMU in the field of international project management. What is more, the entire University has become a well-recognised entity in the area of (1) education related to artificial intelligence applications in medicine; (2) implementing AI-based analyses for scientific purposes and (3) introducing new technologies supporting medical work. New patterns of cooperation between Data Science and medicine/life science specialists have been established as well as the network of contacts between WMU and other institutions potentially interested in the implementation of the experience acquired during the course of the project for further scientific and/or business cooperation.
Nowadays data science is a strategic element in the development of health care system. Hence, it is essential for medical staff to realize where data science may affect their work since there is a constant growth in the number of such areas and their scope is increasing. Staff without such awareness will not be able to benefit from the development of medical sciences combined with the potential offered by data science which may lead to better diagnostics, fewer medical errors, acceleration of many processes, optimization of staff workload and much more. This process that has already begun, is accelerating every day and can be neither avoided nor ignored. What is more, the lack of staff awareness in the field of data science in medicine may badly affect patients and, as a result, a large part of society.
The primary objective was to establish the Centre of Excellence in Medical Data Science (CEMEDS) at WMU, defined as the team of competent scientists with new research excellence who are familiar with innovative technology and clinical study development at the state-of-the-art level in the fields of medical Big Data, modern biostatistics and clinical database technologies. The secondary objective was to complete the networking gaps between the medical field and institutions with experience in the area of Big Data, Machine Learning, database technologies, information engineering and technology, e-health, medical informatics, mathematics and advanced modern statistics. Our success in this context was based on the series of national and international activities and achievements. Additionally, HeartBIT_4.0 was our first project funded by the European Union, where WMU acted as the leader of an international consortium. With the help of our excellent partners who gave us constant support by sharing their experience, we succeeded in increasing the competence of WMU in the field of international project management. What is more, the entire University has become a well-recognised entity in the area of (1) education related to artificial intelligence applications in medicine; (2) implementing AI-based analyses for scientific purposes and (3) introducing new technologies supporting medical work. New patterns of cooperation between Data Science and medicine/life science specialists have been established as well as the network of contacts between WMU and other institutions potentially interested in the implementation of the experience acquired during the course of the project for further scientific and/or business cooperation.
The project was designed in order to upgrade the research profile of the leading institution, namely Wroclaw Medical University (WMU) represented by the Institute of Heart Diseases. The first and basic step of this process was the transfer of knowledge from our partners, which was the subject of 4 dedicated work packages prepared and conducted separately by each excellent partner. It took over 2 years of online meetings, lectures and practical classes (workshops, laboratories) to increase knowledge in the field of data science of scientists from WMU.
In order to promote the broadening of the university's scientific portfolio through the staff new competences as well as networking, we implemented the dissemination and communication activities which included scientific publications in a peer-reviewed journals, attendance in numerous scientific and non-scientific events (congresses, meetings and summits), participation in panels and webinars (as experts in the field of merging medicine with data science) organising summer school etc..
In order to promote the broadening of the university's scientific portfolio through the staff new competences as well as networking, we implemented the dissemination and communication activities which included scientific publications in a peer-reviewed journals, attendance in numerous scientific and non-scientific events (congresses, meetings and summits), participation in panels and webinars (as experts in the field of merging medicine with data science) organising summer school etc..
The project's achievements are far beyond the planned scope, i.e. the transfer of knowledge on data science from excellent partners to WMU staff. We have learned how to manage an international consortium from the position of a project leader, how to talk to data scientists and how to create algorithms on the basis of acquired medical data. Our partners who were initially not familiar with the medical environment, learned how to work with definitely more diverse and more complex data in comparison to datasets analytics professionals usually deal with. We can share our knowledge by conducting dedicated courses aimed to increase the awareness of young doctors about the revolution that is fundamentally changing the medicine thanks to data science. Our experience resulted in numerous invitations to panels of experts and co-authors of chapters of books referring to AI in medicine, addressed both to important stakeholders as well as to the scientific community.