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MetaLung: Towards a Secure Architecture for Lung Cancer Patient Care on the Metaverse | IEEE Conference Publication | IEEE Xplore

MetaLung: Towards a Secure Architecture for Lung Cancer Patient Care on the Metaverse


Abstract:

The interest in metaverse applications by existing industries has seen massive growth thanks to the accelerated pace of research in key technological fields and the shift...Show More

Abstract:

The interest in metaverse applications by existing industries has seen massive growth thanks to the accelerated pace of research in key technological fields and the shift towards virtual interactions fueled by the Covid-19 pandemic. One key industry that can benefit from the integration into the metaverse is healthcare. The potential to provide enhanced care for patients affected by multiple health issues, from standard afflictions to more specialized pathologies, is being explored through the fabrication of architectures that can support metaverse applications. In this paper, we focus on the persistent issues of lung cancer detection, monitoring, and treatment, to propose MetaLung, a privacy and integrity-preserving architecture on the metaverse. We discuss the use cases to enable remote patient-doctor interactions, patient constant monitoring, and remote care. By leveraging technologies such as digital twins, edge computing, explainable AI, IoT, and virtual/augmented reality, we propose how the system could provide better assistance to lung cancer patients and suggest individualized treatment plans to the doctors based on their information. In addition, we describe the current implementation state of the AI-based Decision Support System for treatment selection, I3LUNG, and the current state of patient data collection.
Date of Conference: 26-28 June 2023
Date Added to IEEE Xplore: 06 October 2023
ISBN Information:
Conference Location: Kyoto, Japan
Department of Electronic Systems, Aalborg University, Copenhagen, Denmark
Department of Electronic Systems, Aalborg University, Copenhagen, Denmark
MLcube s.r.l., Milano, Italy
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
Department of Medical Oncology, Istituto Nazionale dei Tumori, Milano, Italy
Department of Electronic Systems, Aalborg University, Copenhagen, Denmark
Department of Electronic Systems, Aalborg University, Copenhagen, Denmark

I. Introduction

The metaverse, a rapidly growing concept, offers significant potential for the evolution of Internet and next-generation applications [1] in diverse fields such as gaming, social media, industry, and healthcare [2]. Characterized by immersive, hyper-spatiotemporal, and self-sustaining qualities, the metaverse envisions virtual avatars representing humans, objects, and other entities from the physical world, interacting in real-time within a simulated environment. This environment may emulate the physical world or be entirely synthesized. The recent Covid-19 pandemic has accelerated the development of virtual presence due to restrictions on physical interactions, bringing healthcare and its future advancements to the forefront of research. Consequently, the intersection of the metaverse and healthcare has emerged as a hot topic, with the integration of fundamental technologies such as Digital Twins (DTs), Virtual/Augmented/Mixed Reality (VR, AR, MR), 5G and beyond, IoT devices and sensors, Artificial Intelligence (AI), and distributed ledgers poised to revolutionize and personalize care for patients afflicted by various pathologies [3]. One such pathology is lung cancer, a leading cause of cancer-related mortality among men and women worldwide, accounting for approximately 18% of all cancer deaths in 2020 [4]. The prevalence and lethality of lung cancer have driven extensive research efforts to better understand the disease and develop effective treatments. In this context, the I3LUNG [5] project is at the forefront of developing an AI-based Decision Support System (DSS) to assist clinicians in treating patients with Non-Small-Cell Lung Cancer (NSCLC). Within this project, establishing a flexible environment that facilitates the exchange of ideas among physicians, analysis of data from previous clinical studies and the real world, and storage of patient information has emerged as a priority. In this paper, following the I3LUNG use case, we propose a fully distributed reference architecture for intelligent lung cancer patient care, namely MetaLung. By leveraging existing technologies, we discuss possible applications ranging from virtual consultations, to cancer diagnosis, disease monitoring, and remote treatment planning. Our contributions are threefold:

Department of Electronic Systems, Aalborg University, Copenhagen, Denmark
Department of Electronic Systems, Aalborg University, Copenhagen, Denmark
MLcube s.r.l., Milano, Italy
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
Department of Medical Oncology, Istituto Nazionale dei Tumori, Milano, Italy
Department of Electronic Systems, Aalborg University, Copenhagen, Denmark
Department of Electronic Systems, Aalborg University, Copenhagen, Denmark
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