Brain-derived neurotrophic factor and antidepressant drugs have different but coordinated effects on neuronal turnover, proliferation, and survival in the adult dentate …

M Sairanen, G Lucas, P Ernfors, M Castrén… - Journal of …, 2005 - Soc Neuroscience
Antidepressants increase proliferation of neuronal progenitor cells and expression of brain-derived
neurotrophic factor (BDNF) in the hippocampus. We investigated the role of BDNF …

Activation of the TrkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects

…, G Lucas, E Koponen, M Sairanen… - Journal of …, 2003 - Soc Neuroscience
Recent studies have indicated that exogenously administered neurotrophins produce
antidepressant-like behavioral effects. We have here investigated the role of endogenous brain-…

A novel early pregnancy risk prediction model for gestational diabetes mellitus

…, GP Ross, H Kouru, PF Williams, M Sairanen… - Fetal diagnosis and …, 2019 - karger.com
Introduction: Accurate early risk prediction for gestational diabetes mellitus (GDM) would
target intervention and prevention in women at the highest risk. We evaluated novel biomarker …

[HTML][HTML] Predicting risk of stillbirth and preterm pregnancies with machine learning

A Koivu, M Sairanen - Health information science and systems, 2020 - Springer
Modelling the risk of abnormal pregnancy-related outcomes such as stillbirth and preterm
birth have been proposed in the past. Commonly they utilize maternal demographic and …

Synthetic minority oversampling of vital statistics data with generative adversarial networks

A Koivu, M Sairanen, A Airola… - Journal of the American …, 2020 - academic.oup.com
Objective Minority oversampling is a standard approach used for adjusting the ratio between
the classes on imbalanced data. However, established methods often provide modest …

First trimester prediction of gestational diabetes mellitus: a clinical model based on maternal demographic parameters

…, J Wong, H Kouru, PF Williams, M Sairanen… - Diabetes research and …, 2017 - Elsevier
Aim Develop a first trimester risk prediction model for GDM based on maternal clinical
characteristics in a large metropolitan multi-ethnic population and compare its performance to that …

A first trimester prediction model for gestational diabetes utilizing aneuploidy and pre-eclampsia screening markers

…, H Kouru, PF Williams, M Sairanen… - The Journal of …, 2018 - Taylor & Francis
Objective: We examined whether first trimester aneuploidy and pre-eclampsia screening
markers predict gestational diabetes mellitus (GDM) in a large multi-ethnic cohort and the …

[HTML][HTML] Quality of randomness and node dropout regularization for fitting neural networks

…, JP Kakko, S Mäntyniemi, M Sairanen - Expert Systems with …, 2022 - Elsevier
Quality of randomness in generating random numbers is an attribute manifested by a
sufficiently random process, and a sufficiently large sample size. To assess it, various statistical …

[HTML][HTML] First-trimester maternal serum amino acids and acylcarnitines are significant predictors of gestational diabetes

J Nevalainen, M Sairanen, H Appelblom… - The review of diabetic …, 2016 - ncbi.nlm.nih.gov
BACKGROUND: Current screening methods for gestational diabetes mellitus (GDM) are
insufficient in detecting the risk of GDM in the first trimester of the pregnancy. Recent …

Evaluation of machine learning algorithms for improved risk assessment for Down's syndrome

…, T Korpimäki, P Kivelä, T Pahikkala, M Sairanen - Computers in Biology …, 2018 - Elsevier
Prenatal screening generates a great amount of data that is used for predicting risk of various
disorders. Prenatal risk assessment is based on multiple clinical variables and overall …