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Decision Support for Health (DSH)

Publications (Mark van Gils)

2021

  1. Antikainen, E, Cella, P, Tolonen, A, van Gils, M. SPECT Image Features for Early Detection of Parkinson’s Disease using Machine Learning Methods. Annu Int Conf IEEE Eng Med Biol Soc. 2021;2021 :2773-2777. doi: 10.1109/EMBC46164.2021.9630272. PubMed PMID:34891824 .
  2. Lähteenmäki, J, Vuorinen, AL, Pajula, J, Harno, K, Lehto, M, Niemi, M et al.. Pharmacogenetics of Bleeding and Thromboembolic Events in Direct Oral Anticoagulant Users. Clin Pharmacol Ther. 2021;110 (3):768-776. doi: 10.1002/cpt.2316. PubMed PMID:34043814 .
  3. Lähteenmäki, J, Vuorinen, AL, Pajula, J, Harno, K, Lehto, M, Niemi, M et al.. Integrating data from multiple Finnish biobanks and national health-care registers for retrospective studies: Practical experiences. Scand J Public Health. 2022;50 (4):482-489. doi: 10.1177/14034948211004421. PubMed PMID:33845693 PubMed Central PMC9152591.
  4. Tohka, J, van Gils, M. Evaluation of machine learning algorithms for health and wellness applications: A tutorial. Comput Biol Med. 2021;132 :104324. doi: 10.1016/j.compbiomed.2021.104324. PubMed PMID:33774270 .
  5. Vuorinen, AL, Lehto, M, Niemi, M, Harno, K, Pajula, J, van Gils, M et al.. Pharmacogenetics of Anticoagulation and Clinical Events in Warfarin-Treated Patients: A Register-Based Cohort Study with Biobank Data and National Health Registries in Finland. Clin Epidemiol. 2021;13 :183-195. doi: 10.2147/CLEP.S289031. PubMed PMID:33727862 PubMed Central PMC7954279.

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2020

  1. Posti, JP, Takala, RSK, Raj, R, Luoto, TM, Azurmendi, L, Lagerstedt, L et al.. Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury. Front Neurol. 2020;11 :549527. doi: 10.3389/fneur.2020.549527. PubMed PMID:33192979 PubMed Central PMC7661930.
  2. Rhodius-Meester, HFM, Paajanen, T, Koikkalainen, J, Mahdiani, S, Bruun, M, Baroni, M et al.. cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders. Alzheimers Dement (Amst). 2020;12 (1):e12083. doi: 10.1002/dad2.12083. PubMed PMID:32864411 PubMed Central PMC7446945.
  3. Pekkala, T, Hall, A, Ngandu, T, van Gils, M, Helisalmi, S, Hänninen, T et al.. Detecting Amyloid Positivity in Elderly With Increased Risk of Cognitive Decline. Front Aging Neurosci. 2020;12 :228. doi: 10.3389/fnagi.2020.00228. PubMed PMID:32848707 PubMed Central PMC7406705.
  4. Muurling, M, Rhodius-Meester, HFM, Pärkkä, J, van Gils, M, Frederiksen, KS, Bruun, M et al.. Gait Disturbances are Associated with Increased Cognitive Impairment and Cerebrospinal Fluid Tau Levels in a Memory Clinic Cohort. J Alzheimers Dis. 2020;76 (3):1061-1070. doi: 10.3233/JAD-200225. PubMed PMID:32597806 PubMed Central PMC7505008.
  5. Lagerstedt, L, Azurmendi, L, Tenovuo, O, Katila, AJ, Takala, RSK, Blennow, K et al.. Interleukin 10 and Heart Fatty Acid-Binding Protein as Early Outcome Predictors in Patients With Traumatic Brain Injury. Front Neurol. 2020;11 :376. doi: 10.3389/fneur.2020.00376. PubMed PMID:32581990 PubMed Central PMC7280446.
  6. Hossain, I, Mohammadian, M, Takala, RSK, Tenovuo, O, Azurmendi Gil, L, Frantzén, J et al.. Admission Levels of Total Tau and β-Amyloid Isoforms 1-40 and 1-42 in Predicting the Outcome of Mild Traumatic Brain Injury. Front Neurol. 2020;11 :325. doi: 10.3389/fneur.2020.00325. PubMed PMID:32477238 PubMed Central PMC7237639.
  7. Jääskeläinen, O, Hall, A, Tiainen, M, van Gils, M, Lötjönen, J, Kangas, AJ et al.. Metabolic Profiles Help Discriminate Mild Cognitive Impairment from Dementia Stage in Alzheimer’s Disease. J Alzheimers Dis. 2020;74 (1):277-286. doi: 10.3233/JAD-191226. PubMed PMID:32007958 PubMed Central PMC7175942.

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2019

  1. Livitckaia, K, Koutkias, V, Kouidi, E, van Gils, M, Maglaveras, N, Chouvarda, I et al.. “OPTImAL”: an ontology for patient adherence modeling in physical activity domain. BMC Med Inform Decis Mak. 2019;19 (1):92. doi: 10.1186/s12911-019-0809-9. PubMed PMID:31023322 PubMed Central PMC6485069.
  2. Liedes, H, Lötjönen, J, Kortelainen, JM, Novak, G, van Gils, M, Gordon, MF et al.. Multivariate Prediction of Hippocampal Atrophy in Alzheimer’s Disease. J Alzheimers Dis. 2019;68 (4):1453-1468. doi: 10.3233/JAD-180484. PubMed PMID:30909211 .
  3. Bruun, M, Frederiksen, KS, Rhodius-Meester, HFM, Baroni, M, Gjerum, L, Koikkalainen, J et al.. Impact of a clinical decision support tool on prediction of progression in early-stage dementia: a prospective validation study. Alzheimers Res Ther. 2019;11 (1):25. doi: 10.1186/s13195-019-0482-3. PubMed PMID:30894218 PubMed Central PMC6425602.
  4. Koikkalainen, JR, Rhodius-Meester, HFM, Frederiksen, KS, Bruun, M, Hasselbalch, SG, Baroni, M et al.. Automatically computed rating scales from MRI for patients with cognitive disorders. Eur Radiol. 2019;29 (9):4937-4947. doi: 10.1007/s00330-019-06067-1. PubMed PMID:30796570 .
  5. Posti, JP, Takala, RSK, Lagerstedt, L, Dickens, AM, Hossain, I, Mohammadian, M et al.. Correlation of Blood Biomarkers and Biomarker Panels with Traumatic Findings on Computed Tomography after Traumatic Brain Injury. J Neurotrauma. 2019;36 (14):2178-2189. doi: 10.1089/neu.2018.6254. PubMed PMID:30760178 PubMed Central PMC6909751.
  6. Bruun, M, Koikkalainen, J, Rhodius-Meester, HFM, Baroni, M, Gjerum, L, van Gils, M et al.. Detecting frontotemporal dementia syndromes using MRI biomarkers. Neuroimage Clin. 2019;22 :101711. doi: 10.1016/j.nicl.2019.101711. PubMed PMID:30743135 PubMed Central PMC6369219.
  7. Hall, A, Pekkala, T, Polvikoski, T, van Gils, M, Kivipelto, M, Lötjönen, J et al.. Prediction models for dementia and neuropathology in the oldest old: the Vantaa 85+ cohort study. Alzheimers Res Ther. 2019;11 (1):11. doi: 10.1186/s13195-018-0450-3. PubMed PMID:30670070 PubMed Central PMC6343349.
  8. Bruun, M, Frederiksen, KS, Rhodius-Meester, HFM, Baroni, M, Gjerum, L, Koikkalainen, J et al.. Impact of a Clinical Decision Support Tool on Dementia Diagnostics in Memory Clinics: The PredictND Validation Study. Curr Alzheimer Res. 2019;16 (2):91-101. doi: 10.2174/1567205016666190103152425. PubMed PMID:30605060 .
  9. Hossain, I, Mohammadian, M, Takala, RSK, Tenovuo, O, Lagerstedt, L, Ala-Seppälä, H et al.. Early Levels of Glial Fibrillary Acidic Protein and Neurofilament Light Protein in Predicting the Outcome of Mild Traumatic Brain Injury. J Neurotrauma. 2019;36 (10):1551-1560. doi: 10.1089/neu.2018.5952. PubMed PMID:30489229 .
  10. Umer, A, Mattila, J, Liedes, H, Koikkalainen, J, Lotjonen, J, Katila, A et al.. A Decision Support System for Diagnostics and Treatment Planning in Traumatic Brain Injury. IEEE J Biomed Health Inform. 2019;23 (3):1261-1268. doi: 10.1109/JBHI.2018.2842717. PubMed PMID:29993563 .

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