Thesis topics in Health Informatics – A summary of previous master theses at Karolinska Institutet

Our thesis semester has just started and my fellow classmates and I are in the midst of reading literature and analyzing data (ok, and also sometimes stressing about everything, but you know. That is part of the deal)

Thinking back to last October/November, I remember that some of us had struggles finding a thesis topic. Thus, I went ahead and summarized the thesis topics from the past three years (2017-2019). Maybe you find some inspiration for your research!

– The categories were chosen by just looking at the titles. Thus, please excuse if I put a topic in the wrong category.
– Students can either write their thesis at KI or at Stockholm University (DSV). Topics concerning data science usually will be supervised by DSV (Department of Computer and System Sciences)
– You may (or may not) notice a few mentions of case studies in Sweden (Hint: Karolinska Institutet is situated in Stockholm). This explains the case studies for, Journalen and Janusmed.
– Furthermore, a few of the data science topics focus on adverse drug events (ADEs). While ADEs are of course a very important research topic, these topics may have also been chosen due to the fact that at DSV one can get access to a well pre-processed ADE database. (And let me tell you, not having to be too worried about pre-processing data saves you so much time. We only have a few months to write our thesis after all)

e-Health / Digitalisation topics

  1. Identification of user needs and requirements for a text-mining tool, through user centered design, for users working in a medical device company call-log center
  2. Towards an ontology for trustful mHealth apps
  3. The trusted Blockchain technology: A unique chance for establishing encompassing Personal Health Records? – Prototyping Health Block Case Study
  4. Nursing home residents’ satisfaction: from feature selection to understanding
  5. Evaluation of an Ultrasound Simulator for Educational Purposes in Healthcare
  6. Re-engineering and Digitalisation of a Graphical Assessment Framework for Mobile Health Apps
  7. A unified theory of acceptance and use of technology informed evaluation of an administrative system used in healthcare management
  8. Expectations mismatch – The importance of healthcare experience when designing clinical decision support systems: A qualitative interview study

Tool specific topics

  1. A study of execution engines and languages for computerized clinical practice guidelines: Towards a re-engineering of OpenEHR Guideline Definition Language
  2. Evaluation of Guideline Conformity for User Interface of Medication Prescription Clinical Decision Support Systems: the case of Janus Toolbar
  3. What are patients’ experiences of using Journalen and what improvement suggestions do they have? An analysis of voluntary user feedback about a Swedish patient-accessible electronic health record
  4.  A usability study of ParkWell – a mobile application for self-tracking Parkinson´s disease
  5. Facilitating Technology-based Mental Health Interventions with Mobile Virtual Reality and Wearable Smartwatches
  6. Evaluation of the Compliance of a Knowledge-based Support for Janusmed interactions and Janusmed risk profile with Web Content Accessibility Guidelines 2.0
  7. Use of video consultation in primary care in Sweden: A comparison between video and physical consultation
  8. A qualitative study exploring hearing aid users’ experiences using the Swedish national patient portal and eHealth service Journalen
  9. Evaluation of the Accessibility of an online Clinical Decision Support System by Web Content Accessibility Guidelines (WCAG) 2.0: The case study of Janusmed Knowledgebases

Country specific case studies

  1. Exploring Differences, Similarities of Swedish and South African eHealth Strategies and Possibilities for Creating a Draft for an Evaluation Model of Their Implementation
  2. Factors to consider when implementing mobile technology in hospital settings – a case study at Karolinska Hospital
  3. Electronic Health Record Workarounds in Team-based Care Setting – A qualitative exploratory case study at a Federally Qualified Community Health Center
  4. Towards a framework for eHealth evaluation and monitoring of the implementation of the Swedish national eHealth strategy
  5. The impact of mHealth services on workflow when delivering home care to patients living in rural areas – A comparison of case studies in Sweden and South Africa
  6. Should emergency care data be more visual? A remote usability evaluation of visual representation formats for Emergency Department Information Systems by American physicians
  7. Evaluation of how clinical content, infrastructure and implementation process affect the use of mobile health applications for clinical documentation – two case studies A comparison between South Africa and Sweden
  8. Design, implementation and evaluation of a deviation detection software application based on historical data in a syndromic surveillance system in Sweden: an experimental study
  9. Health care professionals’ experience with Patient Accessible Electronic Health Records in Swedish Psychiatric care: a mixed methodology study
  10. Governance of Electronic Health Records in Sweden and the United States: A Qualitative Case Study
  11. A qualitative study of key stakeholder perspectives on integration of electronic consultations into healthcare in Sweden

Data science topics

  1. Low-Dimensional Medical Concept Representation Learning from MIMIC-III database and Applications in Adverse Drug Event
  2. Classification of ECG signals using random shapelet forests and lazy learners.
  3. The correlations between the parameters of well-being and driving performance – An investigation on how predictive modelling can be used for identifying wellness factors which have an impact on driving performance
  4. Predictive Modelling for the Ovarian cancer diagnosis using platelet-based method
  5. Feature-based classification of temporal data from Electronic Health Records
  6. Unsupervised pre-training of a neural network to detect healthcare-acquired infections using Swedish electronic health records
  7. Actionable Adverse Drug Event Machine Learning Classifiers
  8. The importance of social media mining in pharmacovigilance: How using Natural Language Processing and Machine Learning techniques to actively monitor social media can benefit in early adverse drug events detection and pharmacovigilance
  9. Exploring the clinical relevance of data science predictions: A comparison of the data science features and the medical pathways that underlie adverse drug event predictions
  10. Distance measures for preprocessing of electronic health record data
  11. Application of early random shapelet forest to electrocardiograms for the identification of myocardial infarction
  12. Multi-scale histopathology image classification for prostate cancer using deep learning
  13. Feature optimization of contact map predictions based on inter-residue distances and U-Net++ architecture
  14. Discretization of Sparse,Multivariate TimeSeries for Detection of Adverse Drug Events
  15. Introducing Interpretable Machine Learning for Healthcare: Potentials and Requirements
  16. Segmentation of Gliomas with Gaussian Mixture Models and Saliency Maps
  17. Predicting Adverse Drug Events from Electronic Health Records using Heterogeneous Medical Data Sources
  18. Detecting subtle changes in vital signs to estimate age in pre-term neonatal population – A risk assessment for early neonatal sepsis in neonatal Intensive Care Unit (NICU): A machine learning approach
  19. Feasibility of Implementing Robotic Process Automation for Rule-based Decision Support upon an Electronic Health Record Application – A Study for Sepsis Detection
  20. Constructing physiology-based risk-scores for clinical deterioration in post-ICU patients
  21. Biomarker Discovery and Identification for Colorectal Cancer Regarding Sex Differences with Machine Learning Techniques
  22. Using large-scale electronic health record data to predict delirium in ICU units: An evidence-based machine learning approach


  1. Biomedical and health informatics competencies – A Delphi Study



Title Photo by Erik Flyg, 2019






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