Disease Trajectories from Healthcare Data: Methodologies, Key Results, and Future Perspectives
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Disease trajectories, defined as sequential, directional disease associations, have become an intense research field driven by the availability of electronic population-wide healthcare data and sufficient computational power. Here, we provide an overview of disease trajectory studies with a focus on European work, including ontologies used as well as computational methodologies for the construction of disease trajectories. We also discuss different applications of disease trajectories from descriptive risk identification to disease progression, patient stratification, and personalized predictions using machine learning. We describe challenges and opportunities in the area that eventually will benefit from initiatives such as the European Health Data Space, which, with time, will make it possible to analyze data from cohorts comprising hundreds of millions of patients.
Original language | English |
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Journal | Annual Review of Biomedical Data Science |
Volume | 7 |
Pages (from-to) | 251-276 |
Number of pages | 26 |
ISSN | 2574-3414 |
DOIs | |
Publication status | Published - 2024 |
- Humans, Disease Progression, Machine Learning/trends, Delivery of Health Care, Europe/epidemiology
Research areas
ID: 402754938