Chapter 27 General Learnings From the Horizon 2020 Project BigMedilytics

Roland Roller; Supriyo Chatterjea; Holmer Hemsen; Dimitrios Vogiatzis; Ricard Martínez Martínez; Langs Georg; Simona Rabinovici-Cohen; Wiebke Duettmann; Alex Sangers; Maria-Esther Vidal; Ernestina Menasalvas; Martin Sanchez Marga; Josep Redon; Ana Ferrer-Albero

Chapter 27 General Learnings From the Horizon 2020 Project BigMedilytics

By Roland Roller, German Research Center for Artificial Intelligence (DFKI), Berlin, Germany, roland.roller@dfki.de | Supriyo Chatterjea, Philips Research, Eindhoven (NL), The Netherlands | Holmer Hemsen, German Research Center for Artificial Intelligence (DFKI), Berlin, Germany, holmer.hemsen@dfki.de | Dimitrios Vogiatzis, National Centre for Scientific Research “Demokritos”; The American College of Greece, Deree, dimitrv@iit.demokritos.gr | Ricard Martínez Martínez, Associate Professor of Constitutional Law and Director of the Microsoft Chair of Privacy and Digital Transformation at the University of Valencia. Universitat de València. Avinguda dels Tarongers, s/n València, ricard.martinez@uv.es | Langs Georg, Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria. Contextflow GmbH, Vienna, Austria, georg.langs@meduniwien.ac.at | Simona Rabinovici-Cohen, IBM Research, Israel, simona@il.ibm.com | Wiebke Duettmann, Charitéé – Universitätsmedizin Berlin, Medical Department of Nephrology and Medical Intensive Care, Berlin, Germany, Berlin Institute of Health, Berlin, Germany, wiebke.duettmann@charite.de | Alex Sangers, TNO (Dutch Organization for Applied Scientific Research), P.O. Box 96800, 2509 JE, the Hague, The Netherlands, alex.sangers@tno.nl | Maria-Esther Vidal, Leibniz University of Hannover, Germany | Ernestina Menasalvas, Universidad Politécnica de Madrid (UPM), Spain | Martin Sanchez Marga, Huawei, Germany | Josep Redon, CIBERObn, Instituto de Salud Carlos III, Madrid, Spain, INCLIVA Research Institute. University of Valencia, Spain, josep.redon@uv.es | Ana Ferrer-Albero, INCLIVA Health Research Institute, University of Valencia, Spain

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Published: 08 Jul 2024

Abstract

Big Data, in combination with Artificial Intelligence (AI), has the potential to change and improve processes in medicine. However, these activities/technologies must be developed to promote the trust of all stakeholders: patients, healthcare professionals, private and public providers, and businesses. Providing a trustworthy AI – lawful, ethical, and robust – requires significant efforts. Although technological development is moving quickly, testing, validation, and integration of such innovation may take many years. The reasons that slow down this process are manifold. However, some barriers and pitfalls are foreseeable and, therefore, can be taken into account or avoided. In order to support future development and integration of AI and BigData technologies, we present technical challenges and lessons learned from our previous project, BigMedilytics, involving clinicians and data scientists. This chapter considers the challenges data scientists providing advanced technology in the healthcare domain may face, along with some suggestions to address any related issues if applicable.