Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Yunendah Nur Fuadah"'
Autor:
Muhammad Adnan Pramudito, Yunendah Nur Fuadah, Ali Ikhsanul Qauli, Aroli Marcellinus, Ki Moo Lim
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract The Comprehensive In-vitro Proarrhythmia Assay (CiPA) initiative aims to refine the assessment of drug-induced torsades de pointes (TdP) risk, utilizing computational models to predict cardiac drug toxicity. Despite advancements in machine l
Externí odkaz:
https://doaj.org/article/72eb694cfceb43bab85ca7bb9da9ad16
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Continuous blood pressure (BP) monitoring is essential for managing cardiovascular disease. However, existing devices often require expert handling, highlighting the need for alternative methods to simplify the process. Researchers have deve
Externí odkaz:
https://doaj.org/article/101dbc5e847240d9a613ba53160fc085
Autor:
Yunendah Nur Fuadah, Ali Ikhsanul Qauli, Aroli Marcellinus, Muhammad Adnan Pramudito, Ki Moo Lim
Publikováno v:
Frontiers in Physiology, Vol 14 (2023)
Introduction: Predicting ventricular arrhythmia Torsade de Pointes (TdP) caused by drug-induced cardiotoxicity is essential in drug development. Several studies used single biomarkers such as qNet and Repolarization Abnormality (RA) in a single cardi
Externí odkaz:
https://doaj.org/article/d9dfbfd90db64896963cec7925a30d82
Publikováno v:
Diagnostics, Vol 13, Iss 15, p 2566 (2023)
Researchers commonly use continuous noninvasive blood-pressure measurement (cNIBP) based on photoplethysmography (PPG) signals to monitor blood pressure conveniently. However, the performance of the system still needs to be improved. Accuracy and pre
Externí odkaz:
https://doaj.org/article/fe800a4dca8040efa201082a9a7ddf25
Autor:
YUNENDAH NUR FUADAH, IBNU DAWAN UBAIDULLAH, NUR IBRAHIM, FAUZI FRAHMA TALININGSING, NIDAAN KHOFIYA SY, MUHAMMAD ADNAN PRAMUDITHO
Publikováno v:
Jurnal Elkomika, Vol 10, Iss 3 (2022)
ABSTRAK Pada penelitian ini dilakukan perancangan arsitektur Convolutional Neural Network (CNN) yang terdiri dari 5 layer konvolusi dan 1-fully connected layer untuk mengklasifikasikan citra fundus kedalam kondisi normal, early, moderate, deep, dan
Externí odkaz:
https://doaj.org/article/01d56dc71652401f836d6742b77e06b4
Autor:
Yunendah Nur Fuadah, Ki Moo Lim
Publikováno v:
Frontiers in Physiology, Vol 12 (2022)
Cardiovascular disorders, including atrial fibrillation (AF) and congestive heart failure (CHF), are the significant causes of mortality worldwide. The diagnosis of cardiovascular disorders is heavily reliant on ECG signals. Therefore, extracting sig
Externí odkaz:
https://doaj.org/article/dc613acb531b4e24920cbff48241d95d
Publikováno v:
Bioengineering, Vol 10, Iss 1, p 45 (2022)
Heart-sound auscultation is one of the most widely used approaches for detecting cardiovascular disorders. Diagnosing abnormalities of heart sound using a stethoscope depends on the physician’s skill and judgment. Several studies have shown promisi
Externí odkaz:
https://doaj.org/article/d126f07c5d5742d3a409f89248fb5c12
Autor:
Yunendah Nur Fuadah, Ki Moo Lim
Publikováno v:
Diagnostics, Vol 12, Iss 11, p 2886 (2022)
Hypertension is a severe public health issue worldwide that significantly increases the risk of cardiac vascular disease, stroke, brain hemorrhage, and renal dysfunction. Early screening of blood pressure (BP) levels is essential to prevent the dange
Externí odkaz:
https://doaj.org/article/9be8c09e1ab34c47bec751de8e60243a
Autor:
Achmad Rizal, Inung Wijayanto, Sugondo Hadiyoso, Yunendah Nur Fuadah, Ki Moo Lim, Triwiyanto Triwiyanto
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789819902477
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46886b42841d393bfa5d921b8d5ec4d5
https://doi.org/10.1007/978-981-99-0248-4_23
https://doi.org/10.1007/978-981-99-0248-4_23
Autor:
Yunendah Nur Fuadah, Ki Moo Lim
Publikováno v:
Electronics; Volume 11; Issue 15; Pages: 2456
Atrial fibrillation (AF) and congestive heart failure (CHF) are the most prevalent types of cardiovascular disorders as the leading cause of death due to delayed diagnosis. Early diagnosis of these cardiac conditions is possible by manually analyzing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3be1f895c49dc2efbe002aa437fe8af1