Maria Paraskevopoulo

Maria Paraskevopoulous headshot

Maria Paraskevopoulou

Meet Maria Paraskevopoulou, data scientist at the Health Economics Unit.

Maria is a highly skilled data scientist with extensive experience in both cognitive neuroscience and psychiatry research, specifically in the areas of neurodevelopmental and addiction disorders. Her PhD in medical sciences from Radboud University provided her with valuable experience in collaborating with fellow researchers and clinicians, as well as statistical analysis of behavioural and functional MRI data and publishing scientific papers.

Maria is passionate about working with the NHS to apply her expertise and research experience to inform healthcare decision-making and improve patient outcomes. She is a driven individual who is motivated by the idea of making a positive impact in healthcare, particularly in the understanding and prevention of diseases. As a key part of the Health Economics Unit team, Maria brings a passion for improvement and working in partnership with healthcare providers in the NHS, advancing health economics.

Meet the rest of our passionate team.

Selected publications

  • Brynte C, Aeschlimann M, Barta C. et al. (2022) ‘The clinical course of comorbid substance use disorder and attention deficit/hyperactivity disorder: protocol and clinical characteristics of the INCAS study’ BMC Psychiatry 22, 625 (2022). https://doi.org/10.1186/s12888-022-04259-6
  • Paraskevopoulou M, van Rooij D, Schene AH, Batalla A, Chauvin R, Buitelaar JK, Schellekens AFA. (2022) ‘Effects of family history of substance use disorder on reward processing in adolescents with and without attention-deficit/hyperactivity disorder’ Addiction Biology . 2022 Mar;27(2):e13137. doi: 10.1111/adb.13137. PMID: 35229951; PMCID: PMC9285350. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9285350
  • Paraskevopoulou M, van Rooij D, Schene AH, Chauvin R, Buitelaar JK, Schellekens AFA. (2021) ‘Effects of substance misuse on inhibitory control in patients with attention-deficit/hyperactivity disorder’ Addiction Biology 2022 Jan;27(1):e13063. doi: 10.1111/adb.13063. Epub 2021 Jun 7. PMID: 34101312; PMCID: PMC9285045. https://pubmed.ncbi.nlm.nih.gov/34101312
  • Novi M, Paraskevopoulou M, van Rooij D, Schene AH, Buitelaar JK, Schellekens AFA. (2021) ‘Effects of substance misuse and current family history of substance use disorder on brain structure in adolescents and young adults with attention-deficit/hyperactivity disorder’ Drug and Alcohol Dependence 2021 Nov 1;228:109032. doi: 10.1016/j.drugalcdep.2021.109032. Epub 2021 Sep 2. PMID: 34555690. https://pubmed.ncbi.nlm.nih.gov/34555690
  • Paraskevopoulou M, van Rooij D, Schene AH, Scheres APJ, Buitelaar JK, Schellekens AFA. (2020) ‘Effects of Substance Misuse and Family History of Substance Use Disorder on Delay Discounting in Adolescents and Young Adults with Attention-Deficit/Hyperactivity Disorder’ European Addiction Research 2020;26(4-5):295-305. doi: 10.1159/000509147. Epub 2020 Jul 13. PMID: 32659779; PMCID: PMC7513619. https://pubmed.ncbi.nlm.nih.gov/32659779
  • Paraskevopoulou M, van Rooij D, Batalla A, Chauvin R, Luijten M, Schene AH, Buitelaar JK, Schellekens AFA. (2020) ‘Effects of substance misuse on reward-processing in patients with attention-deficit/hyperactivity disorder’ Neuropsychopharmacology 46, 622–631 (2021). https://doi.org/10.1038/s41386-020-00896-1 

 

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This is a small selection of all the solutions we can provide.

Evidence generation

Understanding whether new care pathways and interventions are effective, efficient, and deliver value for money

Population health management

Using allocative efficiency techniques and population health analytics to improve value and deliver the best care possible

Advanced analytics

Using advanced techniques in machine learning, data science and casual inference to understand the biggest questions in health

Consultancy

Sharing our vast knowledge to develop NHS capability through training, research design advice and quality assurance