Multiscale modeling of comorbidity relations in hypertensive outpatients
| Autor: | N. Bukhanov, Marina Balakhontceva, Sergey V. Kovalchuk, A.O. Konradi, Nadezhda Zvartau |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Risk analysis Hierarchy (mathematics) business.industry Computer science Disease progression Bayesian network Disease medicine.disease Machine learning computer.software_genre Causality Comorbidity Multiscale modeling 03 medical and health sciences 030104 developmental biology medicine General Earth and Planetary Sciences In patient Artificial intelligence business computer General Environmental Science |
| Zdroj: | Procedia Computer Science. 121:446-450 |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2017.11.060 |
| Popis: | Investigation of comorbidity relations plays crucial role in patients’ stratification and risk analysis. Having a huge dataset of electronic health records of hypertensive outpatients from Federal Almazov North-West Medical Centre, we propose a hierarchical modeling scheme and present our initial results. At each level of disease hierarchy (including time domain), we consider different problems; from causality links to disease progression and optimized treatment. Bayesian networks are used as a main tool for modeling as they are ideal for uncertain and noisy medical high-dimensional datasets. |
| Databáze: | OpenAIRE |
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