The Design and Implementation of a National AI Platform for Public
Healthcare in Italy: Implications for Semantics and Interoperability
- URL: http://arxiv.org/abs/2304.11893v1
- Date: Mon, 24 Apr 2023 08:00:02 GMT
- Title: The Design and Implementation of a National AI Platform for Public
Healthcare in Italy: Implications for Semantics and Interoperability
- Authors: Roberto Reale, Elisabetta Biasin, Alessandro Scardovi, Stefano Toro
- Abstract summary: The Italian National Health Service is adopting Artificial Intelligence through its technical agencies.
Such a vast programme requires special care in formalising the knowledge domain.
Questions have been raised about the impact that AI could have on patients, practitioners, and health systems.
- Score: 62.997667081978825
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The Italian National Health Service is adopting Artificial Intelligence
through its technical agencies, with the twofold objective of supporting and
facilitating the diagnosis and treatment. Such a vast programme requires
special care in formalising the knowledge domain, leveraging domain-specific
data spaces and addressing data governance issues from an interoperability
perspective. The healthcare data governance and interoperability legal
framework is characterised by the interplay of different pieces of legislation.
Data law is the first to be taken into proper account. It primarily includes
the GDPR, the Data Governance Act, and the Open Data Directive. Also, the Data
Act and the European Health Data Space proposals will have an impact on health
data sharing and therefore must be considered as well. The platform developed
by the Italian NHL will have to be integrated in a harmonised manner with the
systems already used in the healthcare system and with the digital assets (data
and software) used by healthcare professionals. Questions have been raised
about the impact that AI could have on patients, practitioners, and health
systems, as well as about its potential risks; therefore, all the parties
involved are called to agree upon to express a common view based on the dual
purpose of improving people's quality of life and keeping the whole healthcare
system sustainable for society as a whole.
Related papers
- Decentralized Health Intelligence Network (DHIN) [0.0]
Decentralized Health Intelligence Network (DHIN) extends the Decentralized Intelligence Network (DIN) framework to address challenges in healthcare data sovereignty and AI utilization.
Building upon DIN's core principles, DHIN introduces healthcare-specific components to tackle data fragmentation across providers and institutions.
It facilitates effective AI utilization by overcoming barriers to accessing diverse health data sources.
arXiv Detail & Related papers (2024-08-12T15:47:26Z) - Multimodal Federated Learning in Healthcare: a Review [5.983768682145731]
Federated Learning (FL) provides a decentralized mechanism where data need not be consolidated.
This paper outlines the current state-of-the-art approaches to Multimodal Federated Learning (MMFL) within the healthcare domain.
It aims to bridge the gap between cutting-edge AI technology and the imperative need for patient data privacy in healthcare applications.
arXiv Detail & Related papers (2023-10-14T19:43:06Z) - FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare [73.78776682247187]
Concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI.
This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare.
arXiv Detail & Related papers (2023-08-11T10:49:05Z) - Blockchain-empowered Federated Learning for Healthcare Metaverses:
User-centric Incentive Mechanism with Optimal Data Freshness [66.3982155172418]
We first design a user-centric privacy-preserving framework based on decentralized Federated Learning (FL) for healthcare metaverses.
We then utilize Age of Information (AoI) as an effective data-freshness metric and propose an AoI-based contract theory model under Prospect Theory (PT) to motivate sensing data sharing.
arXiv Detail & Related papers (2023-07-29T12:54:03Z) - Information Governance as a Socio-Technical Process in the Development
of Trustworthy Healthcare AI [0.0]
Information Governance (IG) processes govern the use of personal confidential data.
Legal basis for data sharing is explicit only for the purpose of delivering patient care.
IG work should start early in the design life cycle and will likely continue throughout.
arXiv Detail & Related papers (2023-01-04T10:21:46Z) - Reliable and Resilient AI and IoT-based Personalised Healthcare
Services: A Survey [1.581123237785583]
This paper conducts a comprehensive survey on personalized healthcare services.
We first present an overview of key requirements of comprehensive personalized healthcare services in modern healthcare Internet of Things (HIoT)
Second, we explored a fundamental three-layer architecture for IoT-based healthcare systems using AI and non-AI-based approaches.
Third, we highlighted different security threats against each layer of IoT architecture along with the possible AI and non-AI-based solutions.
arXiv Detail & Related papers (2022-08-29T23:14:02Z) - MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence
using Federated Evaluation [110.31526448744096]
We argue that unlocking this potential requires a systematic way to measure the performance of medical AI models on large-scale heterogeneous data.
We are building MedPerf, an open framework for benchmarking machine learning in the medical domain.
arXiv Detail & Related papers (2021-09-29T18:09:41Z) - User-Centric Health Data Using Self-sovereign Identities [69.50862982117127]
This article presents the potential use of the issuers Self-Sovereign Identities (SSI) and Distributed Ledger Technologies (DLT) to improve the privacy and control of health data.
The paper lists the prominent use cases of decentralized identities in the health area, and discusses an effective blockchain-based architecture.
arXiv Detail & Related papers (2021-07-26T17:09:52Z) - Using a Personal Health Library-Enabled mHealth Recommender System for
Self-Management of Diabetes Among Underserved Populations: Use Case for
Knowledge Graphs and Linked Data [0.11470070927586014]
This paper reports the implementation of a mobile health digital intervention that incorporates both digital health data stored in patients PHLs and other sources of contextual knowledge.
We describe the technological infrastructures used to construct, manage, and integrate the types of knowledge stored in the PHL.
The proposed PHL helps patients and their caregivers take a central role in making decisions regarding their health.
arXiv Detail & Related papers (2021-03-16T20:43:17Z) - Assessing the Severity of Health States based on Social Media Posts [62.52087340582502]
We propose a multiview learning framework that models both the textual content as well as contextual-information to assess the severity of the user's health state.
The diverse NLU views demonstrate its effectiveness on both the tasks and as well as on the individual disease to assess a user's health.
arXiv Detail & Related papers (2020-09-21T03:45:14Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.