Artificial Intelligence for Hospital Health Care: Application Cases and Answers to Challenges in European Hospitals

Klumpp, Matthias; Hintze, Marcus; Immonen, Milla; Ródenas-Rigla, Francisco; Pilati, Francesco; Aparicio-Martínez, Fernando; Çelebi, Dilay; Liebig, Thomas; Jirstrand, Mats; Urbann, Oliver; Hedman, Marja; Lipponen, Jukka A.; Bicciato, Silvio; Radan, Anda-Petronela; Valdivieso, Bernardo; Thronicke, Wolfgang; Gunopulos, Dimitrios; Delgado-Gonzalo, Ricard

The development and implementation of artificial intelligence (AI) applications in health care contexts is a concurrent research and management question. Especially for hospitals, the expectations regarding improved efficiency and effectiveness by the introduction of novel AI applications are huge. However, experiences with real-life AI use cases are still scarce. As a first step towards structuring and comparing such experiences, this paper is presenting a comparative approach from nine European hospitals and eleven different use cases with possible application areas and benefits of hospital AI technologies. This is structured as a current review and opinion article from a diverse range of researchers and health care professionals. This contributes to important improvement options also for pandemic crises challenges, e.g., the current COVID-19 situation. The expected advantages as well as challenges regarding data protection, privacy, or human acceptance are reported. Altogether, the diversity of application cases is a core characteristic of AI applications in hospitals, and this requires a specific approach for successful implementation in the health care sector. This can include specialized solutions for hospitals regarding human–computer interaction, data management, and communication in AI implementation projects.