Mette Langaas

Professor

Norwegian University of Science and Technology

Norway

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About

Professor Mette Langaas is a faculty member at the Norwegian University of Science and Technology, located in Norway. Her research focuses on cardiovascular disease risk prediction using advanced statistical learning and explainable artificial intelligence, as well as the genetic and hormonal factors associated with obesity. Additionally, she investigates mental health issues, including substance use disorders and their risk factors, utilizing innovative methodologies to analyze complex data. Her recent work includes studies on the intersection of genetics and mental health, as well as exploring the accuracy of published research findings.

Articles (12)

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2025

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2025

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2025

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2023

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2023

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2023

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2022

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2022

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2021

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2021

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2021

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2020

Collaborators (8)

Inga Strümke

Norwegian University of Science and Technology

NORWAY

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Anja Bye

Norwegian University of Science and Technology (NTNU)

NORWAY

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Sang Won Bae

Assistant Professor

Stevens Institute of Technology

UNITED STATES

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Jo Røislien

Full professor

University of Stavanger

NORWAY

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Taylor A. Braund

Postdoctoral Fellow

Black Dog Institute

AUSTRALIA

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Andrew DeWan

Associate Professor of Epidemiology (Chronic Diseases)

Yale School of Public Health

UNITED STATES

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Jasmin Vassileva

Associate Professor

Virginia Commonwealth University

UNITED STATES

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Thea Bjørnland

Associate Professor

Norwegian Institute of Science and Technology

NORWAY

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Mette Langaas

Research Interests

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About

Articles (12)

Sex-specific cardiovascular disease risk prediction using statistical learning and explainable artificial intelligence: the HUNT Study

Exploring associations between the FTO rs9939609 genotype and plasma concentrations of appetite-related hormones in adults with obesity

Symptoms of the suicide crisis syndrome and associated risk factors in an acute psychiatric population, a cross-sectional study

Saddlepoint approximations to score test statistics in logistic regression for analyzing genome‐wide association studies

Mobile Assessments of Mood, Cognition, Smartphone-Based Sensor Activity, and Variability in Craving and Substance Use in Patients With Substance Use Disorders in Norway: Prospective Observational Feasibility Study

Inferring feature importance with uncertainties with application to large genotype data

Clusters

Predicting Relapse in Substance Use: Prospective Modeling Based on Intensive Longitudinal Data on Mental Health, Cognition, and Craving

ADHD and Mental Health Symptoms in the Identification of Young Adults with Increased Risk of Alcohol Dependency in the General Population—The HUNT4 Population Study

The fat mass and obesity-associated (FTO) gene allele rs9939609 and glucose tolerance, hepatic and total insulin sensitivity, in adults with obesity

What proportion of published research findings are false?

Computationally efficient familywise error rate control in genome‐wide association studies using score tests for generalized linear models

Collaborators (8)

Inga Strümke

Anja Bye

Sang Won Bae

Jo Røislien

Taylor A. Braund

Andrew DeWan

Jasmin Vassileva

Thea Bjørnland

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