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Part 1: Document Description
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Citation |
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Title: |
Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology department |
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Identification Number: |
doi:10.48788/DVUA/VHVDAJ |
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Distributor: |
DataverseUA |
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Date of Distribution: |
2026-07-20 |
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Version: |
1 |
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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 |
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Citation |
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Title: |
Cerebrovascular Patients Data for Prognosis — collection of anonymized data about patients in the cardiology department |
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Identification Number: |
doi:10.48788/DVUA/VHVDAJ |
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Authoring Entity: |
Denkov, Ivan (V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine) |
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Software used in Production: |
Python |
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Software used in Production: |
Visual Studio Code |
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Grant Number: |
0125U001129 |
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Distributor: |
DataverseUA |
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Access Authority: |
Denkov, Ivan |
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Depositor: |
Denkov, Ivan |
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Date of Deposit: |
2026-07-03 |
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Holdings Information: |
https://doi.org/10.48788/DVUA/VHVDAJ |
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Study Scope |
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Keywords: |
Computer and Information Science, classification problem, naive Bayes classifier, structural risk, overfitting, computational efficiency, feature space dimensionality, parallel computing |
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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. |
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Time Period: |
2013-01-02-2023-03-31 |
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Date of Collection: |
2026-01-04-2026-01-04 |
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Kind of Data: |
CSV file |
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Methodology and Processing |
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Sources Statement |
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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. |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
Тульчинський В. Г., Денков І. Д. Ефективний баєсівський класифікатор для великої кількості атрибутів : препринт. 2026. Архів препринтів НАН України. |
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Identification Number: |
10.71942/2m49-6745 |
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Bibliographic Citation: |
Тульчинський В. Г., Денков І. Д. Ефективний баєсівський класифікатор для великої кількості атрибутів : препринт. 2026. Архів препринтів НАН України. |
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Label: |
ReadMe.txt |
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Notes: |
text/plain |
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Label: |
sparse_vectors_patients.csv |
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Notes: |
text/comma-separated-values |