Hospital 4.0 and Its Innovation in Methodologies and Technologies

Afferni, Pierangelo; Merone, Mario; Soda, Paolo

doi:10.1109/cbms.2018.00065

Cited by 18 publications

(12 citation statements)

References 18 publications

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“…In fact, the focus changed from the effectiveness of each particular function to the effectiveness of the comprehensive service as perceived by the patient. 87 Moreover, the Internet of things and the Internet of service may help this revolution ensures connectivity and data exchange. Thus, hospital 4.0 can create new opportunities and innovative research areas.…”

Section: Discussion and Future Research Directionsmentioning

confidence: 99%

A review on simulation-based metamodeling in emergency healthcare: methodology, applications, and future challenges

Sahlaoui,

Aboueljinane,

Lebbar

2023

SIMULATION

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Simulation-based metamodels or surrogate models are simplified models that capture the relationship between inputs and outputs of the simulation model. The analytical expression of metamodels is defined using a sample of input/output points obtained from the simulation model. This analytical expression is then embedded in an optimization process that usually provides solutions much faster than other simulation-based optimization techniques such as metaheuristics or mathematical modeling. The goal of this paper is to describe the simulation-based metamodeling approach and to provide a thorough review of the literature on its applications to emergency healthcare systems. For this purpose, we examine the recent literature (journals and conference proceedings) published in the last 15 years (2008–2022). Finally, we identify findings and avenues of research in simulation-based metamodeling that deserve special attention from the scientific community and allow the potential of this approach to be used for better decision-making in emergency healthcare.

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Section: Discussion and Future Research Directionsmentioning

confidence: 99%

A review on simulation-based metamodeling in emergency healthcare: methodology, applications, and future challenges

Sahlaoui,

Aboueljinane,

Lebbar

2023

SIMULATION

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“…Considering that, worldwide, OP affects about 200 million people and causes more than 8.9 million fractures annually, resulting in an OP fracture every 3 seconds, appropriate protocols for patient screening, diagnosis, and monitoring in addition to telemedicine programs are mandatory [ 6 , 7 ]. This is particularly true in this moment [ 5 , 8 ], especially considering the unknown long-term effects of COVID-19 infection on bone metabolism [ 9 , 10 ].…”

Section: Op Management In the Covid-19 Eramentioning

confidence: 99%

“…Out of necessity, we are running fast toward the concept of hospital 4.0 without being fully prepared for the concept, where hospitals have the main task of treating acute patients, while chronic patients must be managed in their home with limited access to places of care [ 8 ]. With suspended and/or limited dual-energy X-ray absorptiometry (DXA) services in an effort to avoid exposing patients to clinical spaces, bone density (BMD) assessment for OP patients could be complex [ 11 ].…”

Section: Op Management In the Covid-19 Eramentioning

confidence: 99%

Blood factors as biomarkers in osteoporosis: points from the COVID-19 era

Salamanna

Maglio

Borsari

et al. 2021

Trends in Endocrinology & Metabolism

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The restrictions adopted during the coronavirus disease 2019 (COVID-19) pandemic limiting direct medical consultations and access to healthcare centers reduced the participation of patients with chronic diseases, such as osteoporosis (OP), in screening and monitoring programs. This highlighted the need for new screening diagnostic tools that are clinically effective, but require minimal technical and time commitments, to stratify populations and identify who is more at risk for OP and related complications. This paper provides an overview of the potential use of blood-related factors, such as platelet (PLT)- and monocyte-related factors, as biomarkers able to quickly screen, detect, and monitor OP in both sexes. Such biomarkers might be of key importance not only during the COVID-19 pandemic but also, even more importantly, during periods of better global health stability.

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“…Artificial intelligence (AI) in particular, with its capabilities and promises, is among the main drivers of the Fourth Industrial Revolution, which is set to transform all sectors, including that of healthcare (Health 4.0). Health 4.0 relies on Industry 4.0 concepts and principles, characterised by increased interconnectivity between cyber and physical elements and solutions based on disruptive information and communication technologies (ICTs) (e.g., big data and the Internet of Things), to shift from hospital-centred to patient-centred organisations and services [2][3][4]. Developments in medical technology are occurring faster than ever before, with Healthcare 5.0 already being the new desirable frontier in terms of smart disease control and detection, smart health monitoring and management and virtual care, relying on emerging digital technologies (e.g., nanotechnology, 5G technologies, robotics, IoT, big data, AI, cloud computing, etc.).…”

Section: Introductionmentioning

confidence: 99%

Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices

Maccaro,

Stokes,

Statham

et al. 2024

JPM

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The use of AI in healthcare has sparked much debate among philosophers, ethicists, regulators and policymakers who raised concerns about the implications of such technologies. The presented scoping review captures the progression of the ethical and legal debate and the proposed ethical frameworks available concerning the use of AI-based medical technologies, capturing key themes across a wide range of medical contexts. The ethical dimensions are synthesised in order to produce a coherent ethical framework for AI-based medical technologies, highlighting how transparency, accountability, confidentiality, autonomy, trust and fairness are the top six recurrent ethical issues. The literature also highlighted how it is essential to increase ethical awareness through interdisciplinary research, such that researchers, AI developers and regulators have the necessary education/competence or networks and tools to ensure proper consideration of ethical matters in the conception and design of new AI technologies and their norms. Interdisciplinarity throughout research, regulation and implementation will help ensure AI-based medical devices are ethical, clinically effective and safe. Achieving these goals will facilitate successful translation of AI into healthcare systems, which currently is lagging behind other sectors, to ensure timely achievement of health benefits to patients and the public.

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Hospital 4.0 and Its Innovation in Methodologies and Technologies

Cited by 18 publications

References 18 publications

A review on simulation-based metamodeling in emergency healthcare: methodology, applications, and future challenges

A review on simulation-based metamodeling in emergency healthcare: methodology, applications, and future challenges

Blood factors as biomarkers in osteoporosis: points from the COVID-19 era

Clearing the Fog: A Scoping Literature Review on the Ethical Issues Surrounding Artificial Intelligence-Based Medical Devices

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