ArticleProceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine2022
An AI based digital-twin for prioritising pneumonia patient treatment.
Article in Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 32 citations in OpenAlex.
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- Artificial intelligence in mechanical ventilation: a narrative review of clinical applications and research gaps.Journal of thoracic disease · 2026Review
- Digital twins in pulmonary medicine: a scoping review of applications, benefits, and challenges.BMC pulmonary medicine · 2026Article
- AKI-twinX: explainable organ structured digital twin for sepsis AKI trajectory forecasting.medRxiv : the preprint server for health sciences · 2026Article
- Application of Digital Twin Technology to Enhance Chronic Diseases Management: A Systematic Review.International journal of telemedicine and applications · 2026Review
- A scoping review of human digital twins in healthcare applications and usage patterns.NPJ digital medicine · 2025Article
- Machine learning model optimization for flood susceptibility zonation over the Kosi megafan, Himalayan foreland basin, India.Scientific reports · 2025Article
- Digital Twins for Clinical and Operational Decision-Making: Scoping Review.Journal of medical Internet research · 2025Article
- Definitions and Characteristics of Patient Digital Twins Being Developed for Clinical Use: Scoping Review.Journal of medical Internet research · 2024Article
- Evolution of digital twins in precision health applications: a scoping review study.Research square · 2024Article
- Model-driven engineering for digital twins: a graph model-based patient simulation application.Frontiers in physiology · 2024Article
- Maternal and fetal health in the digital twin era.Frontiers in pediatrics · 2023Article
- Development and usability testing of a patient digital twin for critical care education: a mixed methods study.Frontiers in medicine · 2023Article
- Digital twin applications in adult critical care: A scoping review of current development and implementation trends.Digital healthReview
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A digital-twin based three-tiered system is proposed to prioritise patients for urgent intensive care and ventilator support. The deep learning methods are used to build patient-specific digital-twins to identify and prioritise critical cases amongst severe pneumonia patients. The three-tiered strategy is proposed to generate severity indices to: (1) identify urgent cases, (2) assign critical care and mechanical ventilation, and (3) discontinue mechanical ventilation and critical care at the optimal time. The severity indices calculated in the present study are the probability of death and the probability of requiring mechanical ventilation. These enable the generation of patient prioritisation lists and facilitates the smooth flow of patients in and out of Intensive Therapy Units (ITUs). The proposed digital-twin is built on pre-trained deep learning models using data from more than 1895 pneumonia patients. The severity indices calculated in the present study are assessed using the standard benchmark of Area Under Receiving Operating Characteristic Curve (AUROC). The results indicate that the ITU and mechanical ventilation can be prioritised correctly to an AUROC value as high as 0.89. This model may be employed in its current form to COVID-19 patients, but transfer learning with COVID-19 patient data will improve the predictions. The digital-twin model developed and tested is available via accompanying Supplemental material.
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