Challenges and opportunities in uncertainty quantification for healthcare and biological systems DOI Creative Commons
Louise Kimpton, L. Mihaela Păun, Mitchel J. Colebank

et al.

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2025, Volume and Issue: 383(2292)

Published: March 13, 2025

Uncertainty quantification (UQ) is an essential aspect of computational modelling and statistical prediction. Multiple applications, including geophysics, climate science aerospace engineering, incorporate UQ in the development translation new technologies. In contrast, application to biological healthcare models understudied suffers from several critical knowledge gaps. era personalized medicine, patient-specific modelling, digital twins , a lack understanding appropriate implementation methodology limits success simulation clinical setting. The main contribution our review article emphasize importance current deficiencies frameworks for systems. As introduction special issue on this topic, we provide overview methodologies, their applications non-biological systems gaps opportunities development, as later highlighted by authors publishing issue. This part theme ‘Uncertainty (Part 1)’.

Language: Английский

Challenges and opportunities in uncertainty quantification for healthcare and biological systems DOI Creative Commons
Louise Kimpton, L. Mihaela Păun, Mitchel J. Colebank

et al.

Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal Year: 2025, Volume and Issue: 383(2292)

Published: March 13, 2025

Uncertainty quantification (UQ) is an essential aspect of computational modelling and statistical prediction. Multiple applications, including geophysics, climate science aerospace engineering, incorporate UQ in the development translation new technologies. In contrast, application to biological healthcare models understudied suffers from several critical knowledge gaps. era personalized medicine, patient-specific modelling, digital twins , a lack understanding appropriate implementation methodology limits success simulation clinical setting. The main contribution our review article emphasize importance current deficiencies frameworks for systems. As introduction special issue on this topic, we provide overview methodologies, their applications non-biological systems gaps opportunities development, as later highlighted by authors publishing issue. This part theme ‘Uncertainty (Part 1)’.

Language: Английский

Citations

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