[The Swecrit Biobank, associated clinical registries, and machine learning (artificial intelligence) improve critical care knowledge].

Journal: Lakartidningen
PMID: 37846149

Abstract

The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, trauma, and COVID-19 include more than 150,000 blood samples and descriptions of critically ill patients. These assets provide a unique opportunity to research and improve the care of the most seriously ill patients through biomarker analyses, proteomic studies, and genetic and epigenetic studies using modern machine learning techniques (artificial intelligence). Interested researchers are invited to submit their proposals and participate.

Authors

  • Attila Frigyesi
    Centre for Mathematical Sciences, Mathematical Statistics, Lund University, Lund, Sweden.
  • Maria Lengquist
    doktorand, specialistläkare, institutionen för kliniska vetenskaper, Lunds universitet; intensiv- och perioperativvård, Skånes universitetssjukhus Lund.
  • Patrik Johnsson
    doktorand, specialistläkare, institutionen för kliniska vetenskaper, Lunds universitet; intensiv- och perioperativvård, Skånes universitetssjukhus Malmö.
  • Anna Lybeck
    med dr, överläkare, institutionen för kliniska vetenskaper, Lunds universitet; intensiv- och perioperativvård, Skånes universitetssjukhus Lund.
  • Martin Spångfors
    med dr, specialistsjuksköterska, institutionen för kliniska vetenskaper, Lunds universitet; anestesi och intensivvård, Centralsjukhuset Kristianstad.
  • Levin Helena
    doktorand, institutionen för kliniska vetenskaper, Lunds universitet.
  • Andreas Jakobsson
    Centre for Mathematical Sciences, Mathematical Statistics, Lund University, Lund, Sweden.
  • Hans Friberg
    Department of Clinical Sciences Lund, Intensive and Perioperative Care, Skåne University Hospital, Lund University, Malmö, Sweden.

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