Ricciardi, Carlo (2021) Design, implementation and realization of an integrated platform dedicated to e-public health, for analysing health data and supporting the management control in healthcare companies. [Tesi di dottorato]
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| Item Type: | Tesi di dottorato |
|---|---|
| Resource language: | English |
| Title: | Design, implementation and realization of an integrated platform dedicated to e-public health, for analysing health data and supporting the management control in healthcare companies. |
| Creators: | Creators Email Ricciardi, Carlo carloricciardi.93@gmail.com |
| Date: | 1 February 2021 |
| Number of Pages: | 86 |
| Institution: | Università degli Studi di Napoli Federico II |
| Department: | Scienze Biomediche Avanzate |
| Dottorato: | Scienze biomorfologiche e chirurgiche |
| Ciclo di dottorato: | 33 |
| Coordinatore del Corso di dottorato: | nome email Cuocolo, Alberto cuocolo@unina.it |
| Tutor: | nome email Cesarelli, Mario UNSPECIFIED |
| Date: | 1 February 2021 |
| Number of Pages: | 86 |
| Keywords: | Machine Learning; Business Intelligence; Healthcare. |
| Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-INF/06 - Bioingegneria elettronica e informatica |
| Date Deposited: | 18 Feb 2021 10:32 |
| Last Modified: | 07 Jun 2023 11:09 |
| URI: | http://www.fedoa.unina.it/id/eprint/14026 |
Collection description
In healthcare, the information is a fundamental aspect and the human body is the major source of every kind of data: the challenge is to benefit from this huge amount of unstructured data by applying technologic solutions, called Big Data Analysis, that allows the management of data and the extraction of information through informatic systems. This thesis aims to introduce a technologic solution made up of two open source platforms: Power BI and Knime Analytics Platform. First, the importance, the role and the processes of business intelligence and machine learning in healthcare will be discussed; secondly, the platforms will be described, particularly enhancing their feasibility and capacities. Then, the clinical specialties, where they have been applied, will be shown by highlighting the international literature that have been produced: neurology, cardiology, oncology, fetal-monitoring and others. An application in the current pandemic situation due to SARS-CoV-2 will be described by using more than 50000 records: a cascade of 3 platforms helping health facilities to deal with the current worldwide pandemic. Finally, the advantages, the disadvantages, the limitations and the future developments in this framework will be discussed while the architectural technologic solution containing a data warehouse, a platform to collect data, two platforms to analyse health and management data and the possible applications will be shown.
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