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Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic health records in 420 448 individuals.

Mehrdad A MizaniAshkan DashtbanLaura PaseaQingjia ZengKamlesh KhuntiJonathan ValabhjiJil Billy MamzaHe GaoTamsin MorrisAmitava Banerjee
Published in: BMJ open diabetes research & care (2024)
In the largest study using ML to date in incident T2D, we identified four distinct subtypes, with potential future implications for etiology, therapeutics, and risk prediction.
Keyphrases
  • electronic health record
  • machine learning
  • adverse drug
  • clinical decision support
  • cardiovascular disease
  • small molecule
  • current status
  • risk factors
  • emergency department
  • big data