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Machine learning-based health environmental-clinical risk scores in European children.

Jean-Baptiste GuimbaudAlexandros P SiskosAmrit Kaur SakhiBarbara HeudeEduard SabidóEva BorràsHector KeunJohn WrightJordi JulvezJose UrquizaKristine Bjerve GützkowLeda ChatziMaribel CasasMariona BustamanteMark NieuwenhuijsenMartine VrijheidMónica López-VicenteMontserrat de Castro PascualNikos StratakisOliver RobinsonRegina GrazulevicieneRemy SlamaSilvia AlemanyXavier BasaganaMarc PlantevitRémy CazabetLéa Maitre
Published in: Communications medicine (2024)
Besides their usefulness for epidemiological research, our risk scores show great potential to capture holistic individual level non-hereditary risk associations that can inform practitioners about actionable factors of high-risk children. As in the post-genetic era personalized prevention medicine will focus more and more on modifiable factors, we believe that such integrative approaches will be instrumental in shaping future healthcare paradigms.
Keyphrases
  • healthcare
  • machine learning
  • young adults
  • public health
  • primary care
  • human health
  • gene expression
  • artificial intelligence
  • risk assessment
  • deep learning
  • climate change