Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology departmentdoi:10.48788/DVUA/VHVDAJDataverseUA2026-07-201Denkov, Ivan, 2026, "Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology department", https://doi.org/10.48788/DVUA/VHVDAJ, DataverseUA, V1Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology departmentdoi:10.48788/DVUA/VHVDAJDenkov, IvanPythonVisual Studio Code0125U001129DataverseUADenkov, IvanDenkov, Ivan2026-07-03Computer and Information Scienceclassification problemnaive Bayes classifierstructural riskoverfittingcomputational efficiencyfeature space dimensionalityparallel computingThe dataset includes data from 9544 patients of the cardiology department, obtained from a depersonalized fragment of the Aesculap patient visit database. Each patient's data is represented as a sparse binary 1436-dimensional vector. 1 more dimension is added to each vector - the class label. The dataset is intended for testing, validation and comparative analysis of algorithms that solve the classification problem. The dataset is suitable for use in educational purposes and scientific research.2013-01-022023-03-312026-01-042026-01-04CSV fileA depersonalized fragment of the "Aesculapius" database, which contains the texts of medical reports with information about the anamnesis, diagnoses, and prescribed treatment.Тульчинський В. Г., Денков І. Д. Ефективний баєсівський класифікатор для великої кількості атрибутів : препринт. 2026. Архів препринтів НАН України.10.71942/2m49-6745Тульчинський В. Г., Денков І. Д. Ефективний баєсівський класифікатор для великої кількості атрибутів : препринт. 2026. Архів препринтів НАН України.ReadMe.txttext/plainsparse_vectors_patients.csvtext/comma-separated-values