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Mark van Gils

University of Tampere

Finland

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Research Interests

Cardiology

40%

Health Communication

40%

Cardiometabolic Health

20%

Heart Failure

20%

Drug Safety

20%

Diabetology

10%

Cardiovascular Risk

10%

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Articles20

Blood biomarkers to identify patients with different intracranial lesion combinations after traumatic brain injury

Article Link

Year:

2025

Digitaalisen kaksosteknologian hyödyntäminen terveydenhuollossa

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Year:

2025

Innovative approaches to collecting, aggregating, and analyzing adverse drug events in smart hospitals

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Year:

2025

Development and Clinical Interpretation of an Explainable AI Model for Predicting Patient Pathways in the Emergency Department

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Year:

2025

Cluster Analysis Reveals Subgroups with Different Risk Profiles and Sickness Absence Patterns in an Occupational Health Cohort

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Year:

2025

Walking detection for Parkinson’s disease patients and healthy control subjects measured with a smartphone accelerometer using mean amplitude deviation algorithm

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Year:

2025

Defining functional requirements for a self-management solution for Hypertrophic Cardiomyopathy patients

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Year:

2025

Multilevel modelling for decision support in hypertrophic cardiomyopathy in the SMASH-HCM project

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Year:

2024

ECG-based data-driven solutions for diagnosis and prognosis of cardiovascular diseases

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Year:

2024

Associations of depressive symptoms and psychosocial working conditions with sickness absences in a Finnish cohort of 11,495 employees

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Year:

2024

Transformers for cardiac patient mortality risk prediction from heterogeneous electronic health records

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Year:

2023

CYP3A4*22 may increase bleeding risk in ticagrelor users

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Year:

2023

Value capture and embeddedness in social-purpose-driven ecosystems

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Year:

2023

Artificial intelligence research in the COVend COVID-19 clinical trial project

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Year:

2023

Trajectories of interleukin 10 and heart fatty acid-binding protein levels in traumatic brain injury patients with or without extracranial injuries

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Year:

2023

Assessing fatigue and sleep in chronic diseases using physiological signals from wearables

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Year:

2022

A smart hospital-driven approach to precision pharmacovigilance

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Year:

2022

DiHECO – Digital healthcare ecosystem research and networking

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Year:

2022

Digitally Supported Lifestyle Intervention to Prevent Type 2 Diabetes Through Healthy Habits

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Year:

2022

A Comprehensive User Modeling Framework and a Recommender System for Personalizing Well-Being Related Behavior Change Interventions: Development and Evaluation

Article Link

Year:

2022

Collaborators25

Tunc Asuroglu

University of Tampere

FINLAND

Moncef Gabbouj

University of Tampere

FINLAND

Daniel Aiham GHAZALI

Université de Picardie Jules Verne

FRANCE

Mikko Niemi

FINLAND

Jari Hyttinen

University of Tampere

FINLAND

Anna-Leena Vuorinen

University of Helsinki

FINLAND

Hannu Nieminen

University of Tampere

FINLAND

Jordi Carrabina

Universitat Autònoma de Barcelona (UAB)

SPAIN

Piia Lavikainen

University of Eastern Finland

FINLAND

Peter Hutchinson

Professor of Neurosurgery

University of Cambridge

UNITED KINGDOM

Diego Prior

Universitat Autònoma de Barcelona (UAB)

SPAIN

Annariina Koivu

University of Tampere

FINLAND

Jussi Aleksi Hernesniemi

University of Tampere

FINLAND

Víctor Giménez

Universitat Autònoma de Barcelona (UAB)

SPAIN

Sea Bez

Associate Professor

University of Montpellier

FRANCE

Pedro A. Moreno-Sanchez

University of Tampere

FINLAND

Diogo Branco

Faculdade de Ciências da Universidade de Lisboa

PORTUGAL

Alpo Värri

University of Tampere

FINLAND

Mika Lehto

FINLAND

Antti Vehkaoja

University of Tampere

FINLAND

Antti Kallonen

University of Tampere

FINLAND

Jussi Pihlajamäki

University of Eastern Finland

FINLAND

Josep Rialp

Universitat Autònoma de Barcelona (UAB)

SPAIN

Tanja Tilles‐Tirkkonen

FINLAND

Markus M Forsberg

Research Professor, Preventive and Predictive Health

FINLAND

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