Machine learning to detect Alzheimer's disease with data on drugs and diagnoses.

Journal: The journal of prevention of Alzheimer's disease
PMID:

Abstract

BACKGROUND: Integrating machine learning with medical records offers potential for early detection of Alzheimer's disease (AD), enabling timely interventions.

Authors

  • Johanna Wallensten
    Department of Clinical Sciences, Danderyd Hospital, 18288, Stockholm, Sweden; Academic Primary Health Care Centre, Region Stockholm, Sweden. Electronic address: johanna.wallensten@ki.se.
  • Caroline Wachtler
    Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Sweden.
  • Nenad Bogdanovic
    Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, 17177, Stockholm, Sweden. Electronic address: nenad.bogdanovic@ki.se.
  • Anna Olofsson
    Division of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, 17177, Stockholm, Sweden. Electronic address: anna.olofsson.2@ki.se.
  • Miia Kivipelto
    Institute of Clinical Medicine, Neurology, University of Eastern Finland, Kuopio, Finland.
  • Linus Jönsson
    Lundbeck, Valby, Denmark; Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
  • Predrag Petrovic
    Department of Clinical Neuroscience, Karolinska Institutet, 17177, Stockholm, Sweden; Center for Cognitive and Computational Neurosceince (CCNP), Karolinska Institutet, 17177, Stockholm, Sweden. Electronic address: predrag.petrovic@ki.se.
  • Axel C Carlsson
    Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Huddinge, Sweden; Academic Primary Health Care Centre, Region Stockholm, Stockholm, Sweden. Electronic address: axel.carlsson@ki.se.