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Mood instability in patients with unipolar depression measured using smartphones and the association with measures of wellbeing, recovery and functioning

Nordic journal of psychiatry, 2024-08, Vol.78 (6), p.518-524

2024

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Benefits and harms of structured outdoor physical activity for people with somatic or mental diseases: A systematic review and meta-analysis

Preventive medicine, 2024-06, Vol.183, p.107966-107966, Article 107966

2024

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Using digital phenotyping to classify bipolar disorder and unipolar disorder – exploratory findings using machine learning models

European neuropsychopharmacology, 2024-04, Vol.81, p.12-19

2024

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Exercise-based rehabilitation in and with nature: a scoping review mapping available interventions

Annals of medicine (Helsinki), 2023-12, Vol.55 (2), p.2267083-2267083

2023

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Machine learning guided development of high-performance nano-structured nickel electrodes for alkaline water electrolysis

Applied materials today, 2023-12, Vol.35, p.102005, Article 102005

2023

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Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forces

Physical chemistry chemical physics : PCCP, 2023-09, Vol.25 (37), p.25828-25837

2023

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Unveiling the plating-stripping mechanism in aluminum batteries with imidazolium-based electrolytes: A hierarchical model based on experiments and ab initio simulations

Chemical engineering journal (Lausanne, Switzerland : 1996), 2023-09, Vol.472, p.144995, Article 144995

2023

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Brokering between tenants for an international materials acceleration platform

Matter, 2023-09, Vol.6 (9), p.2647-2665

2023

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Mood instability and activity/energy instability in patients with bipolar disorder according to day-to-day smartphone-based data – An exploratory post hoc study

Journal of affective disorders, 2023-08, Vol.334, p.83-91

2023

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Irritability in bipolar disorder and unipolar disorder measured daily using smartphone‐based data: An exploratory post hoc study

Acta psychiatrica Scandinavica, 2023-06, Vol.147 (6), p.593-602

2023

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Sensitivity analysis methodology for battery degradation models

Electrochimica acta, 2023-01, Vol.439, p.141430, Article 141430

2023

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Transition1x - a dataset for building generalizable reactive machine learning potentials

Scientific data, 2022-12, Vol.9 (1), p.779-779, Article 779

2022

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Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT

Journal of chemical information and modeling, 2022-10, Vol.62 (19), p.4727-4735

2022

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Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder

Journal of affective disorders, 2022-06, Vol.306, p.246-253

2022

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Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks

Machine learning: science and technology, 2022-03, Vol.3 (1), p.15012

2022

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Discriminating between patients with unipolar disorder, bipolar disorder, and healthy control individuals based on voice features collected from naturalistic smartphone calls

Acta psychiatrica Scandinavica, 2022-03, Vol.145 (3), p.255-267

2022

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Local Biomarkers Involved in the Interplay between Obesity and Breast Cancer

Cancers, 2021-12, Vol.13 (24), p.6286

2021

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Voice analyses using smartphone-based data in patients with bipolar disorder, unaffected relatives and healthy control individuals, and during different affective states

International Journal of Bipolar Disorders, 2021-12, Vol.9 (1), p.38-38, Article 38

2021

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Genotype-phenotype correlations and novel molecular insights into the DHX30-associated neurodevelopmental disorders

Genome medicine, 2021-05, Vol.13 (1), p.90-19, Article 90

2021

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Reducing the rate of psychiatric re‐admissions in bipolar disorder using smartphones—The RADMIS trial

Acta psychiatrica Scandinavica, 2021-05, Vol.143 (5), p.453-465

2021

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The effect of smartphone-based monitoring and treatment on the rate and duration of psychiatric readmission in patients with unipolar depressive disorder: The RADMIS randomized controlled trial

Journal of affective disorders, 2021-03, Vol.282, p.354-363

2021

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Daily mobility patterns in patients with bipolar disorder and healthy individuals

Journal of affective disorders, 2021-01, Vol.278, p.413-422

2021

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Smartphone-based activity measurements in patients with newly diagnosed bipolar disorder, unaffected relatives and control individuals

International Journal of Bipolar Disorders, 2020-11, Vol.8 (1), p.32-32, Article 32

2020

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Daily self-reported and automatically generated smartphone-based sleep measurements in patients with newly diagnosed bipolar disorder, unaffected first-degree relatives and healthy control individuals

Evidence-based mental health, 2020-11, Vol.23 (4), p.146-153

2020

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Mood instability in patients with unipolar depression measured using smartphones and the association with measures of wellbeing, recovery and functioning

Benefits and harms of structured outdoor physical activity for people with somatic or mental diseases: A systematic review and meta-analysis

Using digital phenotyping to classify bipolar disorder and unipolar disorder – exploratory findings using machine learning models

Exercise-based rehabilitation in and with nature: a scoping review mapping available interventions

Machine learning guided development of high-performance nano-structured nickel electrodes for alkaline water electrolysis

Graph neural network interatomic potential ensembles with calibrated aleatoric and epistemic uncertainty on energy and forces

Unveiling the plating-stripping mechanism in aluminum batteries with imidazolium-based electrolytes: A hierarchical model based on experiments and ab initio simulations

The effect of smartphone-based monitoring and treatment including clinical feedback versus smartphone-based monitoring without clinical feedback in bipolar disorder: the SmartBipolar trial—a study protocol for a randomized controlled parallel-group trial

Brokering between tenants for an international materials acceleration platform

Mood instability and activity/energy instability in patients with bipolar disorder according to day-to-day smartphone-based data – An exploratory post hoc study

Irritability in bipolar disorder and unipolar disorder measured daily using smartphone‐based data: An exploratory post hoc study

Sensitivity analysis methodology for battery degradation models

Transition1x - a dataset for building generalizable reactive machine learning potentials

Cheap Turns Superior: A Linear Regression-Based Correction Method to Reaction Energy from the DFT

Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder

Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks

Discriminating between patients with unipolar disorder, bipolar disorder, and healthy control individuals based on voice features collected from naturalistic smartphone calls

Local Biomarkers Involved in the Interplay between Obesity and Breast Cancer

Voice analyses using smartphone-based data in patients with bipolar disorder, unaffected relatives and healthy control individuals, and during different affective states

Genotype-phenotype correlations and novel molecular insights into the DHX30-associated neurodevelopmental disorders

Reducing the rate of psychiatric re‐admissions in bipolar disorder using smartphones—The RADMIS trial

The effect of smartphone-based monitoring and treatment on the rate and duration of psychiatric readmission in patients with unipolar depressive disorder: The RADMIS randomized controlled trial

Daily mobility patterns in patients with bipolar disorder and healthy individuals

Smartphone-based activity measurements in patients with newly diagnosed bipolar disorder, unaffected relatives and control individuals

Daily self-reported and automatically generated smartphone-based sleep measurements in patients with newly diagnosed bipolar disorder, unaffected first-degree relatives and healthy control individuals

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