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Industrial Engineering and Business Information Systems (IEBIS)
Industrial Engineering and Business Information Systems (IEBIS)
UTFacultiesBMSDept HBEIEBIS

Miha Lavric

Dr. Miha Lavrič

University of Twente
Faculty of Behavioural, Management and Social Sciences
Department Industrial Engineering and Business Information Systems

P.O. Box 217
7500 AE Enschede
The Netherlands


Room: RA 3333 (Ravelijn)
Tel: +31 53 489 3324
E-mail: m.lavric@utwente.nl

Click here for my LinkedIn profile

 

GENERAL INFORMATION

Miha is a Tech4People funded postdoctoral researcher working primarily on the Tech4People project entitled “Use of predictive modeling tools to aid in the identification of child abuse and neglect, as well as other risks to child health and well-being”. For his research, Miha is analyzing structured and unstructured (e.g. doctors’ and nurses’ free text notes) data that has been collected during regular consultation visits of children between the ages zero and four at regional preventive child health care organizations. The data is provided by the regional public health organization GGD Twente, Enschede.

Miha is also co-supervising BIT students during their bachelor research assignments that involve analysis of healthcare-related structured and unstructured data using prediction modeling and machine learning approaches.

As a part-time ETL Data Researcher at the company Medical Research Data Management B.V (MRDM), Deventer, Miha is also analyzing the Dutch Institute of Clinical Audit (DICA) datasets on colorectal (DSCA) and lung (DLCA) cancer with the purpose of identifying patterns with healthcare improvement potential.

 

RESEARCH

  1. Use of predictive modeling tools to aid in the identification of child abuse and neglect, and other risks to child health and well-being.
  2. Applying data mining and machine learning techniques on national surveys of child health data to identify patterns useful for early detection of autism spectrum disorders.
  3. Identification of patterns with healthcare improvement potential in DICA and IKNL cancer patient datasets.
  4. Investigating the risk of individual re-identification in (partially) anonymized cancer patient datasets.
  5. Analyses of clinical and laboratory parameters for predicting juvenile arthritic disease development over time.
  6. Analyses of clinical and laboratory parameters for predicting unstable inflammatory bowel disease remission and necessity for intensified maintenance therapy.

 

RESEARCH INTERESTS

  1. Predictive modeling in healthcare, disease management and biomedicine
  2. Use of machine learning and advanced statistics in biomedicine and healthcare
  3. Data analytics and text mining

 

BACKGROUND

Miha is originally “more bio” by trade as he holds a B.Sc. in Microbiology/Microbial Ecology and a Ph.D. in Genetics, both from the University of Ljubljana, Slovenia. Following his Ph.D., he worked first as a postdoctoral researcher at the University of Trieste, Italy and later at the University of Muenster/University Hospital Muenster, Germany. For his biomedical research, Miha started with extensive use of data analysis and data mining software for analyzing microarray gene expression data that he collected from avian or mammal host cells that were exposed to bacteria, viruses (e.g. avian flu) or their constitutive components. Later on, Miha used his data analysis skill for biomarker discovery and clinical evaluation of biomarkers for seronegative arthritis, juvenile rheumatic diseases, and inflammatory bowel disease. Miha is now applying his analytical experience in the Tech4People project problem setting while learning ETL tricks-of-the-trade and coding in Python and R.

 

WORK EXPERIENCE AND EDUCATION

 

PUBLICATIONS

Journal articles (published):

 

Journal articles (submitted):

 

Journal articles (in preparation):

 

NETWORKS

 

OTHER ACTIVITIES

ETL Data Researcher (part-time) @ Medical Research Data Management B.V (MRDM), Deventer

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