ArticleBioengineering (Basel, Switzerland)2023
Metaverse and Healthcare: Machine Learning-Enabled Digital Twins of Cancer.
Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Digital Twin Technology In Radiology.Journal of imaging informatics in medicine · 2026Review
- Gamified Versus Nongamified Metaverse Learning for Breast Health Knowledge in Women: Randomized Controlled Trial.JMIR serious games · 2026Article
- Artificial intelligence-driven multimodal fusion for precision diagnosis and personalized management of breast cancer.Oncology reviews · 2026Review
- Recent Advances and Emerging Directions in Machine Learning-Based Breast Cancer Drug Discovery: A Comprehensive Review.Breast cancer (Dove Medical Press) · 2026Review
- Integrating the Metaverse Into Medical Practice: A Systematic Review of Its Potential and Applications.International journal of telemedicine and applications · 2026Review
- Metaverse in surgery - origins and future potential.Nature reviews. Urology · 2026Review
- The Use of Metaverse in Radiology: A Systematic Review.Health science reports · 2025Review
- From virtual to reality: innovative practices of digital twins in tumor therapy.Journal of translational medicine · 2025Review
- Digital twins in healthcare: a comprehensive review and future directions.Frontiers in digital health · 2025Review
- NurseVerse: nursing in the metaverse era.Frontiers in medicine · 2025Review
- Article
- Definitions and Characteristics of Patient Digital Twins Being Developed for Clinical Use: Scoping Review.Journal of medical Internet research · 2024Article
- Digital Twins' Advancements and Applications in Healthcare, Towards Precision Medicine.Journal of personalized medicine · 2024Review
- Recent Advances in Artificial Intelligence to Improve Immunotherapy and the Use of Digital Twins to Identify Prognosis of Patients with Solid Tumors.International journal of molecular sciences · 2024Review
- Navigating the Metaverse: A New Virtual Tool with Promising Real Benefits for Breast Cancer Patients.Journal of clinical medicine · 2024Review
- Envisioning the Future of Personalized Medicine: Role and Realities of Digital Twins.Journal of medical Internet research · 2024Article
- Leveraging the Metaverse for Enhanced Longevity as a Component of Health 4.0.Mayo Clinic proceedings. Digital health · 2024Review
- Artificial intelligence across oncology specialties: current applications and emerging tools.BMJ oncology · 2024Review
- Exploring Disparities in Healthcare Wearable Use among Cardiovascular Patients: Findings from a National Survey.Reviews in cardiovascular medicine · 2023Article
- Predicting Chronic Hyperplastic Candidiasis Retro-Angular Mucosa Using Machine Learning.Clinics and practice · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medical digital twins, which represent medical assets, play a crucial role in connecting the physical world to the metaverse, enabling patients to access virtual medical services and experience immersive interactions with the real world. One serious disease that can be diagnosed and treated using this technology is cancer. However, the digitalization of such diseases for use in the metaverse is a highly complex process. To address this, this study aims to use machine learning (ML) techniques to create real-time and reliable digital twins of cancer for diagnostic and therapeutic purposes. The study focuses on four classical ML techniques that are simple and fast for medical specialists without extensive Artificial Intelligence (AI) knowledge, and meet the requirements of the Internet of Medical Things (IoMT) in terms of latency and cost. The case study focuses on breast cancer (BC), the second most prevalent form of cancer worldwide. The study also presents a comprehensive conceptual framework to illustrate the process of creating digital twins of cancer, and demonstrates the feasibility and reliability of these digital twins in monitoring, diagnosing, and predicting medical parameters.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.