A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.

<p>A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Miray Gunay Bulut (20714911) (author)
مؤلفون آخرون: Sencer Unal (20714914) (author), Mohamed Hammad (10431225) (author), Paweł Pławiak (17328063) (author)
منشور في: 2025
الموضوعات:
الوسوم: إضافة وسم
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_version_ 1852022779416674304
author Miray Gunay Bulut (20714911)
author2 Sencer Unal (20714914)
Mohamed Hammad (10431225)
Paweł Pławiak (17328063)
author2_role author
author
author
author_facet Miray Gunay Bulut (20714911)
Sencer Unal (20714914)
Mohamed Hammad (10431225)
Paweł Pławiak (17328063)
author_role author
dc.creator.none.fl_str_mv Miray Gunay Bulut (20714911)
Sencer Unal (20714914)
Mohamed Hammad (10431225)
Paweł Pławiak (17328063)
dc.date.none.fl_str_mv 2025-02-12T18:26:19Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0314154.t004
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/A_comparison_of_studies_developed_for_the_detection_of_cardiovascular_diseases_from_signals_obtained_from_wearable_devices_with_machine_learning_methods_/28402027
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Medicine
Cell Biology
Physiology
Cancer
Space Science
Biological Sciences not elsewhere classified
provide earlier diagnoses
premature atrial contractions
massachusetts medical center
like atrial fibrillation
ppg signal data
div >< p
cardiac rhythm disorders
proposed model achieved
raw ppg signals
ppg signals using
1d cnn model
rhythm disorders
cnn model
ppg signals
ventricular fibrillation
deep cnn
wearable devices
vf ),
various ways
sudden death
significant role
second segments
recent years
holter monitors
heart rate
health status
extrasystole ).
different areas
continuously monitor
bandpass filter
balanced circulation
allow doctors
accuracy values
accuracy rate
dc.title.none.fl_str_mv A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <p>A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.</p>
eu_rights_str_mv openAccess
id Manara_bbfcdffc2d865e06ff1dc68bba02997c
identifier_str_mv 10.1371/journal.pone.0314154.t004
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/28402027
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.Miray Gunay Bulut (20714911)Sencer Unal (20714914)Mohamed Hammad (10431225)Paweł Pławiak (17328063)MedicineCell BiologyPhysiologyCancerSpace ScienceBiological Sciences not elsewhere classifiedprovide earlier diagnosespremature atrial contractionsmassachusetts medical centerlike atrial fibrillationppg signal datadiv >< pcardiac rhythm disordersproposed model achievedraw ppg signalsppg signals using1d cnn modelrhythm disorderscnn modelppg signalsventricular fibrillationdeep cnnwearable devicesvf ),various wayssudden deathsignificant rolesecond segmentsrecent yearsholter monitorsheart ratehealth statusextrasystole ).different areascontinuously monitorbandpass filterbalanced circulationallow doctorsaccuracy valuesaccuracy rate<p>A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.</p>2025-02-12T18:26:19ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0314154.t004https://figshare.com/articles/dataset/A_comparison_of_studies_developed_for_the_detection_of_cardiovascular_diseases_from_signals_obtained_from_wearable_devices_with_machine_learning_methods_/28402027CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/284020272025-02-12T18:26:19Z
spellingShingle A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
Miray Gunay Bulut (20714911)
Medicine
Cell Biology
Physiology
Cancer
Space Science
Biological Sciences not elsewhere classified
provide earlier diagnoses
premature atrial contractions
massachusetts medical center
like atrial fibrillation
ppg signal data
div >< p
cardiac rhythm disorders
proposed model achieved
raw ppg signals
ppg signals using
1d cnn model
rhythm disorders
cnn model
ppg signals
ventricular fibrillation
deep cnn
wearable devices
vf ),
various ways
sudden death
significant role
second segments
recent years
holter monitors
heart rate
health status
extrasystole ).
different areas
continuously monitor
bandpass filter
balanced circulation
allow doctors
accuracy values
accuracy rate
status_str publishedVersion
title A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
title_full A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
title_fullStr A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
title_full_unstemmed A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
title_short A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
title_sort A comparison of studies developed for the detection of cardiovascular diseases from signals obtained from wearable devices with machine learning methods.
topic Medicine
Cell Biology
Physiology
Cancer
Space Science
Biological Sciences not elsewhere classified
provide earlier diagnoses
premature atrial contractions
massachusetts medical center
like atrial fibrillation
ppg signal data
div >< p
cardiac rhythm disorders
proposed model achieved
raw ppg signals
ppg signals using
1d cnn model
rhythm disorders
cnn model
ppg signals
ventricular fibrillation
deep cnn
wearable devices
vf ),
various ways
sudden death
significant role
second segments
recent years
holter monitors
heart rate
health status
extrasystole ).
different areas
continuously monitor
bandpass filter
balanced circulation
allow doctors
accuracy values
accuracy rate