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Authors: Luigi Lella 1 ; Ignazio Licata 1 and Christian Pristipino 2

Affiliations: 1 ISEM, Ins. For Scientific Methodology, PA, Italy ; 2 Interventional and Emergency Cardiology Unit, San Filippo Neri –ASL Roma 1, Rome, Italy

Keyword(s): Healthcare Management Systems, Data Mining, Data Analysis, Decision Support Systems.

Abstract: The AIEHEM project aims to analyze the data made available by the regional health system, using an unorganized Turing machine model (A-Type) trained with a swarm-evolutionary hybrid algorithm. The goal is to identify the main factors related to certain outcomes that the healthcare organization intends to achieve (which can be economic, organizational, social or environmental). The chosen AI model is used to enhance, not to replace the analytical capabilities of the healthcare system management. The insights of the AI model are in fact used not only to identify the main objects of study to be taken into consideration, but also to define the areas of intervention and consequently also the stakeholders to be involved in the organizational change project to be carried out through the Theory of Change methodology. AI is therefore used to identify the most suitable ecosystem for solving the considered problem.

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Paper citation in several formats:
Lella, L.; Licata, I. and Pristipino, C. (2023). Artificial Intelligence Enabled Healthcare Ecosystem Model: AIEHEM Project. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF; ISBN 978-989-758-631-6; ISSN 2184-4305, SciTePress, pages 232-238. DOI: 10.5220/0011604300003414

@conference{healthinf23,
author={Luigi Lella. and Ignazio Licata. and Christian Pristipino.},
title={Artificial Intelligence Enabled Healthcare Ecosystem Model: AIEHEM Project},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF},
year={2023},
pages={232-238},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011604300003414},
isbn={978-989-758-631-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF
TI - Artificial Intelligence Enabled Healthcare Ecosystem Model: AIEHEM Project
SN - 978-989-758-631-6
IS - 2184-4305
AU - Lella, L.
AU - Licata, I.
AU - Pristipino, C.
PY - 2023
SP - 232
EP - 238
DO - 10.5220/0011604300003414
PB - SciTePress

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