From 2016-2020, Marco Spruit has been the principle investigator in the Applied Data Science Lab, where his research primarily focused on Self-Service Data Science.

Please refer to my Research Theme page for more information, or my Research Projects page for active projects in this theme.

Top 5 Projects

  1. COVIDA: Computing Visits Data for Dutch Natural Language Processing in Mental Healthcare. EUR 230K (2019-2021). Two-year postdoc, parttime scientific programmer, and deployment infrastructure. Financer(s): Alliance Fund UU-UMCU-TU/e. Applicant(s): Spruit,M., Scheepers,F., & Kaymak,U. et al. Remark: Grant total: 492K EUR.
  2. OPERAMOPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly. EUR 250K (2015-2020). PhD and postdoc position for the STRIP Assistant (STRIPA) prescriptive analytics platform. Financer: PHC 17-2014. Remark: #634238; grant total: 6.6M EUR.
  3. SMESEC: Protecting Small and Medium-sized Enterprises digital technology through an innovative cyber-SECurity framework. EUR 280K (2017-2020). Two PhD positions for cybersecurity maturity modelling. Financer: H2020-DS-2016-2017. Remark: #740787; grant total: 5.6M EUR.
  4. SAF21: Social Aspects in 21st Century Fisheries. EUR 200K (2015–2018). PhD Project on Natural Language Processing (NLP) applications for a Ph.D student stationed at Manchester Metropolitan University (MMU). Financer: MSCA-ITN-2014-ETN. Remark: #642080; grant total: 2.7M EUR.
  5. STRIMP: Implementatie van de STRIP Assistent ter verbetering van de STRIP medicatiebeoordeling. EUR 110K (2018-2019). Postdoc to integrate the STRIP Assistant within Dutch daily primary care. Financer: ZonMW/Goed Gebruik Geneesmiddelen – Stimulering Toepassing In de Praktijk (GGG – STIP Ronde 3). Remark: Grant total: 350K EUR.

Top 5 Publications

  1. Spruit,M., & Lytras,M. (2018). Applied Data Science in Patient-centric Healthcare: Adaptive Analytic Systems for Empowering Physicians and Patients. Telematics and Informatics, 35(4), 643–653. [IF: 3.714] [pdf] [online]
  2. Menger,V., Scheepers,F., & Spruit,M. (2018). Comparing Deep Learning and Classical Machine Learning Approaches for Predicting Inpatient Violence Incidents from Clinical Text. Applied Sciences, 8(6), Data Analytics in Smart Healthcare, 981. [IF: 2.217] [pdf]
  3. Tawfik,N., & Spruit,M. (2020). Evaluating Sentence Representations for Biomedical Text: Methods and Experimental Results. Journal of Biomedical Informatics, 104(April), 103396. [IF: 2.95] [pdf] [online]
  4. Syed,S., Borit,M., & Spruit,M. (2018). Narrow lenses for capturing the complexity of fisheries: A topic analysis of fisheries science from 1990 to 2016. Fish and Fisheries, 1–19. [IF: 6.665] [pdf] [online]
  5. Meulendijk,M., Spruit,M., Drenth-van Maanen,C., Numans,M., Brinkkemper,S., Jansen,P., & Knol,W (2015). Computerized decision support improves medication review effectiveness: an experiment evaluating the STRIP Assistant’s usability. Drugs & Aging, 32(6), 495–503. [IF: 2.846] [pdf] [online]


Subpages (2): Projects & Team Team