Faglige interesser
- Kunstig intelligens og maskinlæring
- Maskinsyn
- Medisinsk teknologi
- Bevissthetsfilosofi
- Algoritmeteori
- Konkurranseprogrammering og -modellering
Undervisning
Bakgrunn
- 2016 - MSc, Informatikk: Programmering og nettverk, UiO
- 2014 - BSc, Informatikk: Programmering og nettverk, UiO
Emneord:
Senter for livsløpsendringer i hjerne og kognisjon
Publikasjoner
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Iakunchykova, Olena; Leonardsen, Esten Høyland & Wang, Yunpeng
(2024).
Genetic evidence for causal effects of immune dysfunction in psychiatric disorders: where are we?
Translational Psychiatry.
ISSN 2158-3188.
14(1),
s. 1–11.
doi:
10.1038/s41398-024-02778-2.
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Persson, Karin Ester Torun; Leonardsen, Esten Høyland; Edwin, Trine Holt; Knapskog, Anne-Brita; Tangen, Gro Gujord & Selbæk, Geir
[Vis alle 9 forfattere av denne artikkelen]
(2023).
Diagnostic accuracy of brain age prediction in a memory clinic population and comparison with clinically available volumetric measures.
Scientific Reports.
ISSN 2045-2322.
13.
doi:
10.1038/s41598-023-42354-0.
Fulltekst i vitenarkiv
Vis sammendrag
The aim of this study was to assess the diagnostic validity of a deep learning-based method estimating brain age based on magnetic resonance imaging (MRI) and to compare it with volumetrics obtained using NeuroQuant (NQ) in a clinical cohort. Brain age prediction was performed on minimally processed MRI data using deep convolutional neural networks and an independent training set. The brain age gap (difference between chronological and biological age) was calculated, and volumetrics were performed in 110 patients with dementia (Alzheimer’s disease, frontotemporal dementia (FTD), and dementia with Lewy bodies), and 122 with non-dementia (subjective and mild cognitive impairment). Area-under-the-curve (AUC) based on receiver operating characteristics and logistic regression analyses were performed. The mean age was 67.1 (9.5) years and 48.7% (113) were females. The dementia versus non-dementia sensitivity and specificity of the volumetric measures exceeded 80% and yielded higher AUCs compared to BAG. The explained variance of the prediction of diagnostic stage increased when BAG was added to the volumetrics. Further, BAG separated patients with FTD from other dementia etiologies with > 80% sensitivity and specificity. NQ volumetrics outperformed BAG in terms of diagnostic discriminatory power but the two methods provided complementary information, and BAG discriminated FTD from other dementia etiologies.
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Leonardsen, Esten Høyland; Peng, Han; Kaufmann, Tobias; Agartz, Ingrid; Andreassen, Ole & Celius, Elisabeth Gulowsen
[Vis alle 19 forfattere av denne artikkelen]
(2022).
Deep neural networks learn general and clinically relevant representations of the ageing brain.
NeuroImage.
ISSN 1053-8119.
256.
doi:
10.1016/j.neuroimage.2022.119210.
Fulltekst i vitenarkiv
Vis sammendrag
The discrepancy between chronological age and the apparent age of the brain based on neuroimaging data — the brain age delta — has emerged as a reliable marker of brain health. With an increasing wealth of data, approaches to tackle heterogeneity in data acquisition are vital. To this end, we compiled raw structural magnetic resonance images into one of the largest and most diverse datasets assembled (n=53542), and trained convolutional neural networks (CNNs) to predict age. We achieved state-of-the-art performance on unseen data from unknown scanners (n=2553), and showed that higher brain age delta is associated with diabetes, alcohol intake and smoking. Using transfer learning, the intermediate representations learned by our model complemented and partly outperformed brain age delta in predicting common brain disorders. Our work shows we can achieve generalizable and biologically plausible brain age predictions using CNNs trained on heterogeneous datasets, and transfer them to clinical use cases.
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Se alle arbeider i Cristin
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Roe, James Michael & Leonardsen, Esten Høyland
(2023).
Brain age as a marker of overall brain health: Phenotypic associations,
genetic foundations and causal relationships.
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Se alle arbeider i Cristin
Publisert
25. jan. 2024 20:42
- Sist endret
25. jan. 2024 20:45