I have a master of science from "The institute of Technology", Linköping University. My exam is in Industrial Engineering and Management with focus in electro- and medical-technology.
In parallel with my research I work at the County Council of Kalmar Landsting with business intelligence and data warehouse. I am also involved in development of automations and integrations for customers of the "Centre for national quality registers - Southeast" (RCSO, Registercentrum Sydost).
Research
I am employed as a doctoral student at the department of computer science and media technology, with affiliation to the research centre Linnaeus University Centre for Data Intensive Sciences and Applications (DISA). I am a member of the eHealth group with focus on: Big data and health information - Reuse of medical data.
My research groups
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E-health – Improved Data to and from Patients The research in the e-health area within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) will result in novel ways for…
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eHealth Institute Linnaeus University researches, evaluates, educates and collaborates with the surrounding society within e-health. Read more about our program and courses, ongoing research projects…
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Linnaeus University Centre for Data Intensive Sciences and Applications The DISA research centre at Linnaeus University focuses its efforts on open questions in collection, analysis and utilization of…
My ongoing research projects
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Doctoral project: Reuse of health data, combing the best of two worlds A method for automatic generation of features with high predictive power based on domain knowledge.
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Project: Prediction of medication risks and drug-related problems Medication related problems is a major problem for society, especially with an ageing population and increasing use of medicines. This…
My completed research projects
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Project: Using past data to prevent future fractures Certain types of medication increase the risk of osteoporosis and fractures. In this research project, we develop a risk assessment tool which can…
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Seed project: Data intensive analysis for identification and prediction of risk medications The main objective for this seed project within Linnaeus University Centre for Data Intensive Sciences and…
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Seed project: Developing the Skeleton Avatar camera Technique (SAT) as a rapid, valid and sensitive measurement of mobility in elderly persons The main objective for this seed project within Linnaeus…
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Seed project: Using Natural Language Models for Extracting Drug-Related Problems (NLMED) The overall goal of the research in this seed project within the Linnaeus University Center for Data Intensive…
Publications
Article in journal (Refereed)
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Björneld, O., Löwe, W. (2024). Real-world validation of a framework for automated knowledge driven feature engineering inspired by medical domain experts. Informatics in Medicine Unlocked. 49.
Status: Published -
Hammar, T., Jonsén, E., Björneld, O., Askfors, Y., Andersson, M.L., et al. (2024). Potential Adverse Drug Events Identified with Decision Support Algorithms from Janusmed Risk Profile : A Retrospective Population-Based Study in a Swedish Region. Pharmacy. 12 (6).
Status: Published -
Björneld, O., Carlsson, M., Löwe, W. (2023). Case study : Feature engineering inspired by domain experts on real world medical data. Intelligence-Based Medicine. 8.
Status: Published -
Nordqvist, O., Björneld, O., Brudin, L., Wanby, P., Nobin, R., et al. (2021). A novel index to assess low energy fracture risks in patients prescribed antiepileptic drugs. PLOS ONE. 16 (8).
Status: Published
Conference paper (Other academic)
- Nordqvist, O., Petersson, A., Björneld, O., Brudin, L., Wanby, P., et al. (2021). Low-energy fracture prediction in patients prescribed antiepileptic drugs : A Swedish case-control study assessing the value of BMD and TBS. Presented at the IOF WCO ESCEO (virtual congress), London, UK, 2021.
- Nordqvist, O., Björneld, O., Brudin, L., Wanby, P., Nobin, R., et al. (2020). A novel index to assess low energy fracture risks in patients prescribed antiepileptic drugs : using real world data from Swedish EHR to create the NEFRI (Nordqvist Epilepsy Fracture Risk Index). Presented at the IOF WCO ESCEO (virtual congress), Barcelona, Spain, 2020.