التفاصيل البيبلوغرافية
| العنوان: |
Disease Trajectories from Healthcare Data: Methodologies, Key Results, and Future Perspectives. |
| المؤلفون: |
Jørgensen IF; Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; email: soren.brunak@cpr.ku.dk., Haue AD; Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; email: soren.brunak@cpr.ku.dk., Placido D; Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; email: soren.brunak@cpr.ku.dk., Hjaltelin JX; Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; email: soren.brunak@cpr.ku.dk., Brunak S; Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; email: soren.brunak@cpr.ku.dk. |
| المصدر: |
Annual review of biomedical data science [Annu Rev Biomed Data Sci] 2024 Aug; Vol. 7 (1), pp. 251-276. |
| نوع المنشور: |
Journal Article; Review |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: Annual Reviews Country of Publication: United States NLM ID: 101714020 Publication Model: Print Cited Medium: Internet ISSN: 2574-3414 (Electronic) Linking ISSN: 25743414 NLM ISO Abbreviation: Annu Rev Biomed Data Sci Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: Palo Alto, CA : Annual Reviews, [2018]- |
| مواضيع طبية MeSH: |
Disease Progression*, Humans ; Machine Learning/trends ; Delivery of Health Care ; Europe/epidemiology |
| مستخلص: |
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. |
| فهرسة مساهمة: |
Keywords: disease co-occurrence; disease trajectories; healthcare data; multimorbidity |
| تواريخ الأحداث: |
Date Created: 20240823 Date Completed: 20240823 Latest Revision: 20240823 |
| رمز التحديث: |
20240826 |
| DOI: |
10.1146/annurev-biodatasci-110123-041001 |
| PMID: |
39178424 |
| قاعدة البيانات: |
MEDLINE |
