RETRACTED: Clustering of comorbidities based on conditional probabilities of diseases in hypertensive patients
| Autor: | N. Bukhanov, A. Semakova, Marina Balakhontceva, Arthur Sabirov, Alexey V. Krikunov, A.O. Konradi, Nadezhda Zvartau |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
medicine.medical_specialty Association rule learning Computer science Conditional probability Bayesian network 030204 cardiovascular system & hematology computer.software_genre Medical research Disease cluster 03 medical and health sciences 030104 developmental biology 0302 clinical medicine medicine General Earth and Planetary Sciences Data mining Intensive care medicine Cluster analysis computer General Environmental Science |
| Zdroj: | ICCS |
| ISSN: | 1877-0509 |
| Popis: | Treatment of chronic diseases, such as arterial hypertension, is always a difficult decision for cardiologist. As the majority of hypertensive patients are of older age, they also have many comorbid diseases. Optimized treatment is supposed to be targeted to the specific cluster of comorbidities. The objective of study is to find effective algorithms for clustering of comorbidities in hypertensive patients. Hierarchical structure of diseases, their types and groups was extracted from text descriptions in EHR database of Federal Almazov North-West Medical Research Centre. Three approaches were tested to find connections between comorbidities: frequency analysis, association rules mining and Bayesian networks. Robust cluster of diseases was found and contains cardiovascular, endocrinological, musculoskeletal and nervous system groups. Further research will be focused on investigating this cluster at the next level of hierarchy and incorporating time scale data of patients’ visits into analysis. |
| Databáze: | OpenAIRE |
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