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 re-ported. 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.

Artificial intelligence for hospital health care: Application cases and answers to challenges in european hospitals / Klumpp, Matthias; Hintze, Marcus; Immonen, Milla; Rodenas-Rigla, Francisco; Pilati, Francesco; Aparicio-Martinez, F.; Celebi, 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. - In: HEALTHCARE. - ISSN 2227-9032. - ELETTRONICO. - 9:8(2021), pp. 961.1-961.24. [10.3390/healthcare9080961]

Artificial intelligence for hospital health care: Application cases and answers to challenges in european hospitals

Pilati, Francesco;
2021-01-01

Abstract

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 re-ported. 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.
2021
8
Klumpp, Matthias; Hintze, Marcus; Immonen, Milla; Rodenas-Rigla, Francisco; Pilati, Francesco; Aparicio-Martinez, F.; Celebi, Dilay; Liebig, Thomas; J...espandi
Artificial intelligence for hospital health care: Application cases and answers to challenges in european hospitals / Klumpp, Matthias; Hintze, Marcus; Immonen, Milla; Rodenas-Rigla, Francisco; Pilati, Francesco; Aparicio-Martinez, F.; Celebi, 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. - In: HEALTHCARE. - ISSN 2227-9032. - ELETTRONICO. - 9:8(2021), pp. 961.1-961.24. [10.3390/healthcare9080961]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/319509
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