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Träfflista för sökning "WFRF:(Hakkinen K) srt2:(2020-2022)"

Sökning: WFRF:(Hakkinen K) > (2020-2022)

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  • Hakkinen, K, et al. (författare)
  • Implementation of CYP2D6 copy-number imputation panel and frequency of key pharmacogenetic variants in Finnish individuals with a psychotic disorder
  • 2022
  • Ingår i: The pharmacogenomics journal. - : Springer Science and Business Media LLC. - 1473-1150 .- 1470-269X. ; 22:3, s. 166-172
  • Tidskriftsartikel (refereegranskat)abstract
    • We demonstrate that CYP2D6 copy-number variation (CNV) can be imputed using existing imputation algorithms. Additionally, we report frequencies of key pharmacogenetic variants in individuals with a psychotic disorder from the genetically bottle-necked population of Finland. We combined GWAS chip and CYP2D6 CNV data from the Breast Cancer Pain Genetics study to construct an imputation panel (n = 902) for CYP2D6 CNV. The resulting data set was used as a CYP2D6 CNV imputation panel in 9262 non-related individuals from the SUPER-Finland study. Based on imputation of 9262 individuals we confirm the higher frequency of CYP2D6 ultrarapid metabolizers and a 22-fold enrichment of the UGT1A1 decreased function variant rs4148323 (UGT1A1*6) in Finland compared with non-Finnish Europeans. Similarly, the NUDT15 variant rs116855232 was highly enriched in Finland. We demonstrate that imputation of CYP2D6 CNV is possible and the methodology enables studying CYP2D6 in large biobanks with genome-wide data.
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  • Bulten, W, et al. (författare)
  • Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
  • 2022
  • Ingår i: Nature medicine. - : Springer Science and Business Media LLC. - 1546-170X .- 1078-8956. ; 28:1, s. 154-
  • Tidskriftsartikel (refereegranskat)abstract
    • Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge—the largest histopathology competition to date, joined by 1,290 developers—to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted κ, 95% confidence interval (CI), 0.840–0.884) and 0.868 (95% CI, 0.835–0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.
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