Use this URL to cite this publication: https://hdl.handle.net/20.500.14911/209702
Classification of cardiovascular diseases using machine learning methods and PQRST intervals segmentation of electrocardiogram records from Holter monitoring
Publication Type (CRIS)
Tezės kitoje duomenų bazėje / Theses in other database (T1c)
Publication Type (eLABa)
Konferencijos pranešimo tezės tarptautinėse DB / Conference presentation abstract in an international DB (T1)
VILNIUS TECH Research Priorities and Topics
Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems (IK0303)
Lithuanian Intelligent Specialization
Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies (L106)
Author(s)
Title
Classification of cardiovascular diseases using machine learning methods and PQRST intervals segmentation of electrocardiogram records from Holter monitoring
Uladzislau Hadalau
Is part of
DAMSS: 15th conference on data analysis methods for software systems, Druskininkai, Lithuania, November 28-30, 2024
Published In
| Year | Start Page | End Page |
|---|---|---|
2024 | 36 | 37 |
Publisher
Vilnius : Vilniaus universiteto leidykla, 2024
Referenced in Database(s)(DBs)
Extent
p. 36-37
Science / Art Area
Technologijos mokslai / Technological sciences (T)
Field of Science / Art
Informatikos inžinerija / Informatics engineering (T007)
Informatika / Informatics (N009)
Matematika / Mathematics (N001)
Resource Type (COAR)
TextConference outputConference proceedingsConference paper
Language
Anglų / English (en)
Country
Lietuva / Lithuania (LT)
File(s)
Owning collection
ISBN (of the container)
9786090711125
eLABa ID
218023775
ISSN
2669-0233
Access Rights
Atviroji prieiga / Open Access
Creative Commons License