Precision diagnostics in children.

children machine learning omics precision diagnostics precision medicine

Journal

Cambridge prisms. Precision medicine
ISSN: 2752-6143
Titre abrégé: Camb Prism Precis Med
Pays: England
ID NLM: 9918609886206676

Informations de publication

Date de publication:
2023
Historique:
received: 16 08 2022
revised: 05 01 2023
accepted: 13 01 2023
medline: 3 2 2023
pubmed: 3 2 2023
entrez: 29 3 2024
Statut: epublish

Résumé

Medical practice is transforming from a reactive to a pro-active and preventive discipline that is underpinned by precision medicine. The advances in technologies in such fields as genomics, proteomics, metabolomics, transcriptomics and artificial intelligence have resulted in a paradigm shift in our understanding of specific diseases in childhood, greatly enhanced by our ability to combine data from changes within cells to the impact of environmental and population changes. Diseases in children have been reclassified as we understand more about their genomic origin and their evolution. Genomic discoveries, additional 'omics' data and advances such as optical genome mapping have driven rapid improvements in the precision and speed of diagnoses of diseases in children and are now being incorporated into newborn screening, have improved targeted therapies in childhood and have supported the development of predictive biomarkers to assess therapeutic impact and determine prognosis in congenital and acquired diseases of childhood. New medical device technologies are facilitating data capture at a population level to support higher diagnostic accuracy and tailored therapies in children according to predicted population outcome, and digital ecosystems now tailor therapies and provide support for their specific needs. By capturing biological and environmental data as early as possible in childhood, we can understand factors that predict disease or maintain health and track changes across a more extensive longitudinal path. Data from multiple health and external sources over long-time periods starting from birth or even in the

Identifiants

pubmed: 38550930
doi: 10.1017/pcm.2023.4
pii: S2752614323000042
pmc: PMC10953773
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

e17

Informations de copyright

© The Author(s) 2023.

Déclaration de conflit d'intérêts

The author declares no conflict of interest.

Auteurs

Paul Dimitri (P)

Department of Paediatric Endocrinology, Sheffield Children's NHS Foundation Trust, Sheffield, UK.
The College of Health, Wellbeing and Life Sciences, Sheffield Hallam University, Sheffield, UK.

Classifications MeSH