The “Safor Salut” cooperation program, a joint initiative between FISABIO–Gandia Health Department, FISABIO–HACLE La Pedrera, Campus Gandia Campus of the Universitat Politècnica de València (UPV) and the Federation of Business Associations of La Safor (FAES, for its Spanish initials), is set to hold a Technology Pill on technology for the early detection of disease and pathologies on Thursday, May 27, from 1:00 p.m. to 2:30 p.m., through the online platform Zoom.
To attend the conference, you must register by filling out the registration form.
The Covid-19 pandemic has highlighted the importance of a robust healthcare system, equipped with the technical resources and means required to to serve the public. A health crisis such as the current one aggravates the problems of waiting lists, slows down lab tests, complicates the situation for chronic patients and reduces doctor visits for ailments other than the coronavirus. Hence the importance of technological solutions to help in the early detection of diseases and pathologies.
There currently exist many devices and applications for this purpose, in addition to the possibility of developing custom-made solutions for each disease, making for improvements in the quality of care and hospital management. “Right now we have the scientific and technological capabilities to solve almost any challenge and integrate disruptive solutions. The only thing we need is to identify the cases of interest,” indicates the Safor Salut technical team.
In this regard, the event aims to provide information to promote the creation of new collaborative research and innovation projects based on this technology on the part of the research staff from Campus Gandia (UPV) and the DS Gandia, Hospital de La Pedrera, businesses from la Safor and patient associations.
To this end, the basic concepts of the existing technology related to early detection (photonic technology, artificial intelligence, apps…) applied to the health sector will be addressed and the existing technological developments and limits will be analyzed by way of examples of successful applications.
1:00 pm. Safor Salut, objectives of the conference and ways to channel challenges and ideas for possible projects related to the early detection of diseases. Safor Salut technical team.
1:10 pm. Early detection of cardiovascular diseases through artificial intelligence. Jose Joaquín Rieta. Campus Gandia (UPV).
1:20 pm. Optical biosensors for the detection of biomarkers for clinical diagnosis. Sergi Beñat Morais. Research Institute for Molecular Recognition and Technological Development (IDM).
1:30 pm. Oxidative Stress Products as emerging tumor markers for colorectal cancer. Guillermo Saéz. Professor of Biochemistry and Molecular Biology. Faculty of Medicine and Dentistry. Clinical Chief of the Clinical Analysis Service of the Dr. Peset University Hospital.
1:40 p.m. Analysis and application of synergies between artificial intelligence and computational neuroscience to improve the understanding and treatment of neurological diseases. Salva Ardid. CIDEGENT researcher of the Gen – T plan. Gandia Campus (UPV).
1:50 pm. The importance of early detection from the perspective of sick people. Patient Association. Spanish Cancer Association of Gandia-Valencia
2:10 pm. Discussion
2:20 pm. Closing of the conference. Ramón Soler. President of FAES.
The conference is aimed at the research staff of Campus Gandia (UPV), staff members form the DS Gandia and the Hospital de la Pedrera interested in proposing improvements in patient care and the overall health of the population through early detection, businesses from the Safor, as well as patient associations, with the aim of proposing and collaborating in finding solutions to these challenges.
NEW IDEAS AND CHALLENGES
If you have an idea for a project or solution related to early detection applied to the healthcare sector and you need a partner from the healthcare, university or business setting to carry it out, submit your idea to saforsalut.es/ideas-retos and we will help you find them.
SAFOR SALUT TEAM
Project funded by: