Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology department (doi:10.48788/DVUA/VHVDAJ)

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Part 2: Study Description
Part 5: Other Study-Related Materials
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Document Description

Citation

Title:

Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology department

Identification Number:

doi:10.48788/DVUA/VHVDAJ

Distributor:

DataverseUA

Date of Distribution:

2026-07-20

Version:

1

Bibliographic Citation:

Denkov, 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, V1

Study Description

Citation

Title:

Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology department

Identification Number:

doi:10.48788/DVUA/VHVDAJ

Authoring Entity:

Denkov, Ivan (V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine)

Software used in Production:

Python

Software used in Production:

Visual Studio Code

Grant Number:

0125U001129

Distributor:

DataverseUA

Access Authority:

Denkov, Ivan

Depositor:

Denkov, Ivan

Date of Deposit:

2026-07-03

Holdings Information:

https://doi.org/10.48788/DVUA/VHVDAJ

Study Scope

Keywords:

Computer and Information Science, classification problem, naive Bayes classifier, structural risk, overfitting, computational efficiency, feature space dimensionality, parallel computing

Abstract:

The 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.

Time Period:

2013-01-02-2023-03-31

Date of Collection:

2026-01-04-2026-01-04

Kind of Data:

CSV file

Methodology and Processing

Sources Statement

Data Sources:

A depersonalized fragment of the "Aesculapius" database, which contains the texts of medical reports with information about the anamnesis, diagnoses, and prescribed treatment.

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Тульчинський В. Г., Денков І. Д. Ефективний баєсівський класифікатор для великої кількості атрибутів : препринт. 2026. Архів препринтів НАН України.

Identification Number:

10.71942/2m49-6745

Bibliographic Citation:

Тульчинський В. Г., Денков І. Д. Ефективний баєсівський класифікатор для великої кількості атрибутів : препринт. 2026. Архів препринтів НАН України.

Other Study-Related Materials

Label:

ReadMe.txt

Notes:

text/plain

Other Study-Related Materials

Label:

sparse_vectors_patients.csv

Notes:

text/comma-separated-values