Dr. M.R. (Marco) Spruit
Universitair hoofddocent
Sleutelpublicaties
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 (Switzerland), 8(6), [981]. https://doi.org/10.3390/app8060981
Tawfik, N., & Spruit, M. (2019). UU_TAILS at 2019 MEDIQA Challenge: Learning Textual Entailment in the Medical Domain. In Proceedings of the BioNLP 2019 workshop (pp. 493–499). Association for Computational Linguistics (ACL). https://www.aclweb.org/anthology/W19-5053.pdf
Spruit, M., & Lytras, M. (Eds.) (2018). Applied Data Science in Patient-centric Healthcare: Adaptive Analytic Systems for Empowering Physicians and Patients. Telematics and Informatics, 35(4), 643–653. https://doi.org/10.1016/j.tele.2018.04.002
Publicaties
2023
Wetenschappelijke publicaties
van Haastrecht, M., Brinkhuis, M., Wools, S., & Spruit, M. (2023). VAST: a practical validation framework for e-assessment solutions. Information Systems and e-Business Management. https://doi.org/10.1007/s10257-023-00641-3
Rijcken, E., Scheepers, F., Zervanou, K., Spruit, M., Mosteiro Romero, P., & Kaymak, U. (Accepted/In press). Towards Interpreting Topic Models with ChatGPT. In The 20th World Congress of the International Fuzzy Systems Association (IFSA 2023) International Fuzzy Systems Association.
Toledo, C. V., Schraagen, M., Dijk, F. V., Brinkhuis, M., & Spruit, M. (2023). Readability Metrics for Machine Translation in Dutch: Google vs. Azure & IBM. Applied Sciences, 13(7), 1-14. [4444]. https://doi.org/10.3390/app13074444
Dijk, F. V., Gadellaa, J., Toledo, C. V., Spruit, M., Brinkkemper, S., & Brinkhuis, M. (2023). Uncovering the structures of privacy research using bibliometric network analysis and topic modelling. Organizational Cybersecurity Journal: Practice, Process and People. https://doi.org/10.1108/OCJ-11-2021-0034
Haastrecht, M. V., Brinkhuis, M., Peichl, J., Remmele, B., & Spruit, M. (2023). Embracing Trustworthiness and Authenticity in the Validation of Learning Analytics Systems. In LAK23: 13ᵗʰ International Learning Analytics and Knowledge Conference (LAK 2023) (pp. 552-558). Association for Computing Machinery. https://doi.org/10.1145/3576050.3576060
2022
Wetenschappelijke publicaties
van Toledo, C., Schraagen, M., van Dijk, F. W., Brinkhuis, M., & Spruit, M. (2022). Exploring the Utility of Dutch Question Answering Datasets for Human Resource Contact Centres. Information, 13(11), 1-11. [513]. https://doi.org/10.3390/info13110513
Sarhan, I., Mosteiro Romero, P., & Spruit, M. (2022). UU-Tax at SemEval-2022 Task 3: Improving the generalizability of language models for taxonomy classification through data augmentation. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022) (pp. 271-281). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.semeval-1.35
Mosteiro Romero, P., Kuiper, J., Masthoff, J., Scheepers, F. E., & Spruit, M. (2022). Bias Discovery in Machine Learning Models for Mental Health. Information, 13(5), 1-15. [237]. https://doi.org/10.3390/info13050237
Rijcken, E., Kaymak, U., Scheepers, F. E., Mosteiro Romero, P., Zervanou, K., & Spruit, M. (2022). Topic Modeling for Interpretable Text Classification From EHRs. Frontiers in Big Data, 5, 1-11. [846930]. https://doi.org/10.3389/fdata.2022.846930
Borger, T., Mosteiro Romero, P., Kaya, H., Rijcken, E., Salah, A., Scheepers, F., & Spruit, M. (2022). Federated learning for violence incident prediction in a simulated cross-institutional psychiatric setting. Expert Systems with Applications, 199, 1-9. [116720]. https://doi.org/10.1016/j.eswa.2022.116720
Sallevelt, B. T. G. M., Huibers, C. J. A., Heij, J. M. J. O., Egberts, T. C. G., van Puijenbroek, E. P., Shen, Z., Spruit, M. R., Jungo, K. T., Rodondi, N., Dalleur, O., Spinewine, A., Jennings, E., O'Mahony, D., Wilting, I., & Knol, W. (2022). Frequency and Acceptance of Clinical Decision Support System-Generated STOPP/START Signals for Hospitalised Older Patients with Polypharmacy and Multimorbidity. Drugs & Aging, 39(1), 59-73. https://doi.org/10.1007/s40266-021-00904-z
2021
Wetenschappelijke publicaties
Felix, S. E. A., Bagheri, A., Ramjankhan, F. R., Spruit, M. R., Oberski, D., De Jonge, N., Van Laake, L. W., Suyker, W. J. L., & Asselbergs, F. W. (2021). A data mining-based cross-industry process for predicting major bleeding in mechanical circulatory support. European Heart Journal - Digital Health, 2(4), 635-642. https://doi.org/10.1093/ehjdh/ztab082
van Haastrecht, M., Golpur, G., Tzismadia, G., Kab, R., Priboi, C., David, D., Răcătăian, A., Brinkhuis, M., & Spruit, M. (2021). A shared cyber threat intelligence solution for smes. Electronics (Switzerland), 10(23), 1-21. [2913]. https://doi.org/10.3390/electronics10232913
Rijcken, E., Scheepers, F. E., Mosteiro Romero, P., Zervanou, K., Spruit, M., & Kaymak, U. (2021). A Comparative Study of Fuzzy Topic Models and LDA in terms of Interpretability. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (SSCI 2021) (pp. 1-8). IEEE. https://doi.org/10.1109/SSCI50451.2021.9660139
Dijk, F. V., Toledo, C. V., Spruit, M., & Brinkhuis, M. J. S. (2021). Pillars of Privacy: Identifying Core Theory in a Network Analysis of Privacy Literature. In ECIS 2021 Research Papers [1420] AIS Electronic Library (AISeL). https://aisel.aisnet.org/ecis2021_rp/84
van Haastrecht, M., Yigit Ozkan, B., Brinkhuis, M., & Spruit, M. (2021). Respite for SMEs: A Systematic Review of Socio-Technical Cybersecurity Metrics. Applied Sciences, 11(15), 1-28. [6909]. https://doi.org/10.3390/app11156909
Mosteiro Romero, P., Rijcken, E., Zervanou, K., Kaymak, U., Scheepers, F. E., & Spruit, M. (2021). Machine Learning for Violence Risk Assessment Using Dutch Clinical Notes. Journal of Artificial Intelligence for Medical Sciences, 2( 1-2), 44-54. https://doi.org/10.2991/jaims.d.210225.001
van Haastrecht, M., Sarhan, I., Yigit Ozkan, B., Brinkhuis, M., & Spruit, M. (2021). SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing. Frontiers in Research Metrics and Analytics, 6, 1-14. [685591]. https://doi.org/10.3389/frma.2021.685591
Shen, Z., & Spruit, M. (2021). Automatic Extraction of Adverse Drug Reactions from Summary of Product Characteristics. Applied Sciences, 11(6), 1-11. [2663]. https://doi.org/10.3390/app11062663
2020
Wetenschappelijke publicaties
van Toledo, C., van Dijk, F. W., & Spruit, M. (2020). Dutch Named Entity Recognition and De-identification Methods for the Human Resource Domain. International Journal on Natural Language Computing, 6(6), 23-34. https://doi.org/10.5121/ijnlc.2020.9602
Toledo, C. V., Dijk, F. V., & Spruit, M. (2020). Evaluating Dutch Named Entity Recognition and De-identification Methods in the Human Resources Domain. In D. C. Wyld, & D. Nagamalai (Eds.), 10th International Conference on Advances in Computing and Information Technology (ACITY 2020), November 28~29, 2020, London, United Kingdom (Vol. 10, pp. 239–249). AIRCC Publishing Corporation. https://doi.org/10.5121/csit.2020.101520
Spruit, M., & Vries, N. D. (2020). Self-Service Data Science for Adverse Event Prediction in Electronic Healthcare Records. In A. Visvizi, M. Lytras, & N. Aljohani (Eds.), Research & Innovation Forum 2020: Disruptive Technologies in Times of Change Springer. https://doi.org/10.1007/978-3-030-62066-0
Tawfik, N., Spruit, M., & Ho Ryu, K. (Ed.) (2020). Computer-Assisted Relevance Assessment: A Case Study of Updating Systematic Medical Reviews. Applied Sciences, 10(8), [2845]. https://doi.org/10.3390/app10082845
Spruit, M., & Ferati, D. (2020). Text Mining Business Policy Documents: Applied Data Science in Finance. International Journal of Business Intelligence Research, 11(2), 1–19. https://doi.org/10.4018/IJBIR.20200701.oa1
Sarhan, I., Spruit, M., Esposito, M., Massala, G. (Ed.), Minutolo, A. (Ed.), & Pota, M. (Ed.) (2020). Can We Survive without Labelled Data in NLP? Transfer Learning for Open Information Extraction. Applied Sciences, 10(17), [5758]. https://doi.org/10.3390/app10175758
Ooms, R., Spruit, M., & Hu, Y. (Ed.) (2020). Self-Service Data Science in Healthcare with Automated Machine Learning. Applied Sciences, 10(9), 1-18. [2992]. https://doi.org/10.3390/app10092992
Meppelink, J., Langen, J. V., Siebes, A., Spruit, M., & Visvizi, A. (2020). Beware Thy Bias: Scaling Mobile Phone Data to Measure Traffic Intensities. Sustainability, 12(9), [3631]. https://doi.org/10.3390/su12093631
Yigit Ozkan, B., & Spruit, M. R. (2020). Addressing SME Characteristics for Designing Information Security Maturity Models. In N. Clarke, & S. Furnell (Eds.), Human Aspects of Information Security and Assurance: 14th IFIP WG 11.12 International Symposium, HAISA 2020, Mytilene, Lesbos, Greece, July 8–10, 2020, Proceedings (IFIP Advances in Information and Communication Technology; Vol. 593). Springer Cham. https://doi.org/10.1007/978-3-030-57404-8_13
Mosteiro Romero, P. J., Rijcken, E., Zervanou, K., Kaymak, U., Scheepers, F., & Spruit, M. (2020). Making sense of violence risk predictions using clinical notes. In Z. Huang, S. Siuly, H. Wang, R. Zhou, & Y. Zhang (Eds.), Health Information Science: 9th International Conference, HIS 2020, Amsterdam, The Netherlands, October 20–23, 2020, Proceedings (pp. 3-14). (Lecture Notes in Computer Science; Vol. 12435). Springer Cham. https://doi.org/10.1007/978-3-030-61951-0_1
Spruit, M., Dedding, T., & Vijlbrief, D. (2020). Self-Service Data Science for Healthcare Professionals: A Data Preparation Approach. In F. Cabitza, A. Fred, & H. Gamboa (Eds.), Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (Vol. 5, pp. 724–734). SciTePress. https://doi.org/10.5220/0009169507240734
Tawfik, N., & Spruit, M. (2020). Evaluating Sentence Representations for Biomedical Text: Methods and Experimental Results. Journal of Biomedical Informatics, 104, [103396]. https://doi.org/10.1016/j.jbi.2020.103396
Omta, W., van Heesbeen, R., Shen, Z., de Nobel, J., van der Velden, L., Medema, R., Siebes, A., Feelders, A., Brinkkemper, S., Klumperman, J., Spruit, M., Brinkhuis, M., & Egan, D. (2020). Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening. SLAS Discovery, 25(6), 655–664. https://doi.org/10.1177/2472555220919345
Lefebvre, A. E. J., Baharak, B., & Spruit, M. R. (2020). Exploring research data management planning challenges in practice. IT - Information Technology. https://doi.org/10.1515/itit-2019-0029
Spruit, M., & Rijnst, S. V. D. (2020). Clinical decision support for infection control in surgical care. In M. Lytras, A. Visvizi, & A. Sarirete (Eds.), Innovation in Health Informatics: a Smart Healthcare Primer (Vol. 1, pp. 101–121). Elsevier. https://doi.org/10.1016/B978-0-12-819043-2.00004-6
Omta, W., Heesbeen, R. V., Shen, I., Feelders, A., Brinkhuis, M., Egan, D., & Spruit, M. (2020). PurifyR: an R Package for highly automated reproducible variable extraction and standardization. Families, Systems and Health, 3(1), 1-7. https://doi.org/10.1089/sysm.2019.0007
2019
Wetenschappelijke publicaties
Yigit Ozkan, B., & Spruit, M. (2019). Cybersecurity Standardization for SMEs: Stakeholders’ Perspectives and a Research Agenda. International Journal of Standardization Research, 17(2), [3]. https://doi.org/10.4018/IJSR.20190701.oa1
Spruit, M., & Linden, V. V. D. (2019). BIDQI: The Business Impacts of Data Quality Interdependencies Model. (Technical Report Series; No. UU-CS-2019-001). UU BETA ICS Departement Informatica.
https://dspace.library.uu.nl/bitstream/handle/1874/390067/ce04d6fd89f811b9947549b6fb7bc7efc6b1.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/390067/ce04d6fd89f811b9947549b6fb7bc7efc6b1.pdf?sequence=1
Lefebvre, A., Berendsen, J., & Spruit, M. (2019). Evaluation of classification models for retrieving experimental sections from full-text publications. (Technical Report Series; No. UU-CS-2019-002). UU BETA ICS Departement Informatica.
https://dspace.library.uu.nl/bitstream/handle/1874/390074/fc69ac9f7fde176881a35430d04834554ac5.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/390074/fc69ac9f7fde176881a35430d04834554ac5.pdf?sequence=1
Spruit, M., Lingen, S., & Yigit Ozkan, B. (2019). The CYSFAM Questionnaire: Assessing CYberSecurity Focus Area Maturity. (Technical Report Series; No. UU-CS-2019-003). UU BETA ICS Departement Informatica.
https://dspace.library.uu.nl/bitstream/handle/1874/390073/2019_003.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/390073/2019_003.pdf?sequence=1
Janssen, J., & Spruit, M. (2019). M-RAM: a Mobile Risk Assessment Method for Enterprise Mobile Security. (Technical Report Series; No. UU-CS-2019-009). UU BETA ICS Departement Informatica.
https://dspace.library.uu.nl/bitstream/handle/1874/390068/2019_009.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/390068/2019_009.pdf?sequence=1
Haan, E. D., Spruit, M., & Zoet, M. (2019). Patterns for Derivation Business Rules. (Technical Report Series; No. UU-CS-2019-010). UU BETA ICS Departement Informatica.
Renes, C., & Spruit, M. (2019). What do you mean? The CIRCA-DIPS method for root cause analysis of data interoperability problems within aviation information systems. (Technical Report Series; No. UU-CS-2019-011). UU BETA ICS Departement Informatica.
Yigit Ozkan, B., & Spruit, M. (2019). A Questionnaire Model for Cybersecurity Maturity Assessment for Critical Infrastructures. In A. Fournaris, K. Lampropoulos, & E. Tordera (Eds.), Information and Operational Technology Security Systems. First International Workshop, IOSec 2018, CIPSEC Project (pp. 49–60). (Lecture notes in computer science; Vol. 11398). Springer. https://doi.org/10.1007/978-3-030-12085-6_5
Tawfik, N., & Spruit, M. (2019). PreMedOnto: A Computer Assisted Ontology for Precision Medicine. In E. Métais, et al. (Ed.), NLDB 2019: International Conference on Applications of Natural Language to Information Systems (Vol. 11608, pp. 329–336). Springer. https://doi.org/10.1007/978-3-030-23281-8_28
Tawfik, N., & Spruit, M. (2019). Towards Recognition of Textual Entailment in the Biomedical Domain. In E. E. A. Métais (Ed.), NLDB 2019: International Conference on Applications of Natural Language to Information Systems (Vol. 11608, pp. 368–375). Springer. https://doi.org/10.1007/978-3-030-23281-8_32
Tawfik, N., & Spruit, M. (2019). UU_TAILS at 2019 MEDIQA Challenge: Learning Textual Entailment in the Medical Domain. In Proceedings of the BioNLP 2019 workshop (pp. 493–499). Association for Computational Linguistics (ACL). https://www.aclweb.org/anthology/W19-5053.pdf
Spruit, M., & Meijers, S. (2019). Big Data for the Masses: The CRISP-DCW Method for Distributed Computing Workflows. In A. Visvizi, & M. Lytras (Eds.), Research & Innovation Forum 2019 (pp. 325–341). Springer.
Spruit, M., & Ferati, D. (2019). Applied Data Science in Financial Industry: Natural Language Processing Techniques for Bank Policies. In A. Visvizi, & M. Lytras (Eds.), Research & Innovation Forum 2019 (pp. 351–367). Springer.
Shen, Z., Wang, X., & Spruit, M. (2019). Big Data Framework for Scalable and Efficient Biomedical Literature Mining in the Cloud. In NLPIR 2019: Proceedings of the 2019 3rd International Conference on Natural Language Processing and Information Retrieval (pp. 80–86). ACM.
Shen, Z., & Spruit, M. (2019). LOCATE: A web application to link open-source clinical software with literature. In R. Moucek, A. Fred, & H. Gamboa (Eds.), Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5 (pp. 294–301). SciTePress. https://doi.org/10.5220/0007378702940301
Sarhan, I., & Spruit, M. (2019). Contextualized Word Embeddings in a Neural Open Information Extraction Model. In E. E. A. Métais (Ed.), NLDB 2019: International Conference on Applications of Natural Language to Information Systems (Vol. 11608, pp. 359–367). Springer. https://doi.org/10.1007/978-3-030-23281-8_31
Menger, V., Spruit, M., Klift, W. V. D., & Scheepers, F. (2019). Using Cluster Ensembles to Identify Psychiatric Patient Subgroups. In D. Riaño, S. Wilk, & A. ten Teije (Eds.), Artificial Intelligence in Medicine (Vol. 11526, pp. 252–262). Springer. https://doi.org/10.1007/978-3-030-21642-9_31
Menger, V., Spruit, M., Bruin, J. D., Kelder, T., & Scheepers, F. (2019). Supporting Reuse of EHR Data in Healthcare Organizations: the CARED Research Infrastructure Framework. In R. Moucek, A. Fred, & H. Gamboa (Eds.), Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5 (pp. 41–50). SciTePress.
Lefebvre, A., & Spruit, M. (2019). A Socio-Technical Perspective on Reproducibility Challenges in Research Data Management. In 13th Mediterranean Conference on Information Systems (Vol. 10). AIS.
Menger, V., Spruit, M., Est, R. V., Nap, E., & Scheepers, F. (2019). Machine Learning Approach to Inpatient Violence Risk Assessment Using Routinely Collected Clinical Notes in Electronic Health Records. JAMA network open, 2(7), [e196709]. https://doi.org/10.1001/jamanetworkopen.2019.6709
https://dspace.library.uu.nl/bitstream/handle/1874/388082/menger_2019_oi_190269.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/388082/menger_2019_oi_190269.pdf?sequence=1
Jungo, et al., K., & Spruit, M. R. (2019). "Optimising PharmacoTherapy In the multimorbid elderly in primary CAre" (OPTICA) to improve medication appropriateness: study protocol of a cluster randomised controlled trial. BMJ Open, 9, e031080. https://doi.org/10.1136/bmjopen-2019-031080
Adam, et al., L., & Spruit, M. R. (2019). Rationale and design of OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people (OPERAM): a cluster randomised controlled trial. BMJ Open, 9, [e026769]. https://doi.org/10.1136/bmjopen-2018-026769
Yigit Ozkan, B., Spruit, M., Wondolleck, R., & Burriel Coll, V. (2019). Modelling adaptive information security for SMEs in a cluster. Journal of Intellectual Capital, 21(2), 325-356. https://doi.org/10.1108/JIC-05-2019-0128
Lefebvre, A., & Spruit, M. (2019). Designing Laboratory Forensics. In I. O. Pappas, J. Krogstie, L. Jaccheri, P. Mikalef, Y. K. Dwivedi, & M. Mäntymäki (Eds.), Digital Transformation for a Sustainable Society in the 21st Century - 18th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2019, Proceedings (pp. 238-251). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11701 LNCS). Springer. https://doi.org/10.1007/978-3-030-29374-1_20
Syed, S., ní Aodha, L., Scougal, C., & Spruit, M. R. (2019). Mapping the global network of fisheries science collaboration. Fish and Fisheries, 20(5), 830-856. https://doi.org/10.1111/faf.12379
https://dspace.library.uu.nl/bitstream/handle/1874/386057/Syed_et_al_2019_Fish_and_Fisheries.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/386057/Syed_et_al_2019_Fish_and_Fisheries.pdf?sequence=1
Shen, Z., van Krimpen, H., & Spruit, M. R. (2019). A lightweight API-based approach for building flexible clinical NLP systems. Journal of Healthcare Engineering, 2019, 1-11. https://doi.org/10.1155/2019/3435609
Shen, Z., Spruit, M., Lytras, M., Chui, K. (Ed.), & Visvizi, A. (Ed.) (2019). A systematic review on open source clinical software on GitHub for improving software reuse in smart healthcare. Applied Sciences, 9(1), [150]. https://doi.org/10.3390/app9010150
Ooms, R., Spruit, M. R., & Overbeek, S. J. (2019). 3PM revisited: Dissecting the Three Phases Method for Outsourcing Knowledge Discovery . International Journal of Business Intelligence Research, 10(1), 80-93. [5]. https://doi.org/10.4018/IJBIR.2019010105
2018
Wetenschappelijke publicaties
Yigit Ozkan, B., & Spruit, M. (2018). Assessing and Improving Cybersecurity Maturity for SMEs: Standardization aspects. In 1st SMESEC Workshop
Seddik Tawfik, N., & Spruit, M. (2018). Automated Contradiction Detection in Biomedical Literature. In P. Perner (Ed.), 14th International Conference on Machine Learning and Data Mining in Pattern Recognition (Vol. 1, pp. 138–148). (Lecture Notes in Computer Science ). Springer. https://doi.org/10.1007/978-3-319-96136-1_12
Sarhan, I., & Spruit, M. (2018). Uncovering Algorithmic Approaches in Open Information Extraction: A Literature Review. In M. Atzmueller, & W. Duivesteijn (Eds.), 30th Benelux Conference on Artificial Intelligence: BNAIC 2018 Preproceedings (pp. 223–234). Springer CSAI / JADS.
Spruit, M., & Adriana, T. (2018). Business Intelligence in Secondary Education: Data-driven Innovation by Quality Measurement. In M. Lytras, L. Daniela, & A. Visvizi (Eds.), Enhancing Knowledge Discovery and Innovation in the Digital Era (pp. 56–90). IGI Global. https://doi.org/10.4018/978-1-5225-4191-2.ch004
Homberg, M. V. D., Monné, R., & Spruit, M. (2018). Bridging the Information Gap: Mapping Data Sets on Information Needs in the Preparedness and Response Phase. In S. Hostettler, S. Najih Besson, & B. J (Eds.), Technologies for Development: From Innovation to Social Impact (pp. 213–225). Springer. https://doi.org/10.1007/978-3-319-91068-0_18
https://dspace.library.uu.nl/bitstream/handle/1874/374299/VanDenHomberg2018_Chapter_BridgingTheInformationGapMappi.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/374299/VanDenHomberg2018_Chapter_BridgingTheInformationGapMappi.pdf?sequence=1
Spruit, M., & Lytras, M. (Eds.) (2018). Applied Data Science in Patient-centric Healthcare: Adaptive Analytic Systems for Empowering Physicians and Patients. Telematics and Informatics, 35(4), 643–653. https://doi.org/10.1016/j.tele.2018.04.002
Seddik Tawfik, N., & Spruit, M. (2018). The SNPCurator: Literature mining of SNP disease association. Database: The Journal of Biological Databases and Curation, 2018(January), bay020. https://doi.org/10.1093/database/bay020
Pieket Weeserik, B., & Spruit, M. (2018). Improving Operational Risk Management using Business Performance Management technologies. Sustainability, 10(3), [640]. https://doi.org/10.3390/su10030640
Homberg, M. V. D., Monné, R., & Spruit, M. (2018). Bridging the information gap of disaster responders by optimizing data selection using cost and quality. Computers and Geosciences, 120, 60–72. https://doi.org/10.1016/j.cageo.2018.06.002
Shen, Z., & Spruit, M. (Accepted/In press). LOCATE: A web application to link open-source clinical software with literature. In 12th International Conference on Health Informatics
Spruit, M. R., & Joosten, P. (Accepted/In press). Managing student engagement in higher education: The case of CURPA. In A. Visvizi, M. Lytras, & A. Sarirete (Eds.), Management and Administration of Higher Education Institutions in Times of change Emerald.
Syed, S., & Spruit, M. R. (2018). Exploring Symmetrical and Asymmetrical Dirichlet Priors for Latent Dirichlet Allocation. International Journal of Semantic Computing, 12(3), 399-423. https://doi.org/10.1142/S1793351X18400184
Lefebvre, A. E. J., Elizabeth Schermerhorn, & Spruit, M. R. (2018). HOW RESEARCH DATA MANAGEMENT CAN CONTRIBUTE TO EFFICIENT AND RELIABLE SCIENCE. In ECIS 2018 Proceedings Collections AIS Electronic Library (AISeL). https://aisel.aisnet.org/ecis2018_rp/35
https://dspace.library.uu.nl/bitstream/handle/1874/371758/1260_doc.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/371758/1260_doc.pdf?sequence=1
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 (Switzerland), 8(6), [981]. https://doi.org/10.3390/app8060981
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, 19(4), 643-661. https://doi.org/10.1111/faf.12280
Zweth, J. V. D., Askari, M., Spruit, M., & Nimwegen, C. V. (2018). Devices used for non-invasive tele homecare for cardiovascular patients: A systematic literature review. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (Vol. 5, pp. 300-307). SciTePress. https://doi.org/10.5220/0006541603000307
Syed, S., & Spruit, M. (2018). Selecting Priors for Latent Dirichlet Allocation. In 12th IEEE International Conference on Semantic Computing (pp. 194-202). IEEE. https://doi.org/10.1109/ICSC.2018.00035
Luchies, E., Spruit, M., & Askari, M. (2018). Speech Technology in the Dutch Health Care: A Qualitative Study. In R. Zwiggelaar, A. Fred, H. Gamboa, & E. S. Bermudez i Badia (Eds.), Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies: HEALTHINF 2018 (Vol. 5, pp. 339-348). SciTePress. https://doi.org/10.5220/0006550103390348
2017
Wetenschappelijke publicaties
Meulendijk, M., Spruit, M., & Brinkkemper, S. (2017). Risk Mediation in Association Rules: Application Examples. (Technical Report Series; No. UU-CS-2017-004). UU BETA ICS Departement Informatica.
https://dspace.library.uu.nl/bitstream/handle/1874/359541/2017_004.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/359541/2017_004.pdf?sequence=1