Ade Iriani Sapitri

According to our database, Ade Iriani Sapitri authored at least 12 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Improved delineation model of a standard 12-lead electrocardiogram based on a deep learning algorithm.

Annisa Darmawahyuni, Siti Nurmaini, Muhammad Naufal Rachmatullah, Prazna Paramitha Avi, Samuel Benedict Putra Teguh, Ade Iriani Sapitri, Bambang Tutuko, Firdaus

BMC Medical Informatics Decis. Mak., December, 2023

Accurate Fetal QRS-Complex Classification from Abdominal Electrocardiogram Using Deep Learning.

Annisa Darmawahyuni, Bambang Tutuko, Siti Nurmaini, Muhammad Naufal Rachmatullah, Muhammad Ardiansyah, Firdaus, Ade Iriani Sapitri, Anggun Islami

Int. J. Comput. Intell. Syst., December, 2023

Automatic echocardiographic anomalies interpretation using a stacked residual-dense network model.

Siti Nurmaini, Ade Iriani Sapitri, Bambang Tutuko, Muhammad Naufal Rachmatullah, Dian Palupi Rini, Annisa Darmawahyuni, Firdaus, Satria Mandala, Ria Nova, Nuswil Bernolian

BMC Bioinform., December, 2023

CervicoXNet: an automated cervicogram interpretation network.

Siti Nurmaini, Muhammad Naufal Rachmatullah, Patiyus Agustiansyah, Radiyati Umi Partan, Bambang Tutuko, Dian Palupi Rini, Annisa Darmawahyuni, Firdaus, Ade Iriani Sapitri, Akhiar Wista Arum

Medical Biol. Eng. Comput., September, 2023

2022

Short Single-Lead ECG Signal Delineation-Based Deep Learning: Implementation in Automatic Atrial Fibrillation Identification.

Bambang Tutuko, Muhammad Naufal Rachmatullah, Annisa Darmawahyuni, Siti Nurmaini, Alexander Edo Tondas, Rossi Passarella, Radiyati Umi Partan, Ahmad Rifai, Ade Iriani Sapitri, Firdaus

Sensors, 2022

Automated Precancerous Lesion Screening Using an Instance Segmentation Technique for Improving Accuracy.

Patiyus Agustiansyah, Siti Nurmaini, Laila Nuranna, Irfannuddin Irfannuddin, Rizal Sanif, Legiran Legiran, Muhammad Naufal Rachmatullah, Gavira Olipa Florina, Ade Iriani Sapitri, Annisa Darmawahyuni

Sensors, 2022

Deep learning-based electrocardiogram rhythm and beat features for heart abnormality classification.

Annisa Darmawahyuni, Siti Nurmaini, Muhammad Naufal Rachmatullah, Bambang Tutuko, Ade Iriani Sapitri, Firdaus, Ahmad Fansyuri, Aldi Predyansyah

PeerJ Comput. Sci., 2022

An improved semantic segmentation with region proposal network for cardiac defect interpretation.

Siti Nurmaini, Bayu Adhi Tama, Muhammad Naufal Rachmatullah, Annisa Darmawahyuni, Ade Iriani Sapitri, Firdaus, Bambang Tutuko

Neural Comput. Appl., 2022

2021

Deep Learning-Based Computer-Aided Fetal Echocardiography: Application to Heart Standard View Segmentation for Congenital Heart Defects Detection.

Siti Nurmaini, Muhammad Naufal Rachmatullah, Ade Iriani Sapitri, Annisa Darmawahyuni, Bambang Tutuko, Firdaus, Radiyati Umi Partan, Nuswil Bernolian

Sensors, 2021

AFibNet: an implementation of atrial fibrillation detection with convolutional neural network.

Bambang Tutuko, Siti Nurmaini, Alexander Edo Tondas, Muhammad Naufal Rachmatullah, Annisa Darmawahyuni, Ria Esafri, Firdaus, Ade Iriani Sapitri

BMC Medical Informatics Decis. Mak., 2021

Beat-to-Beat Electrocardiogram Waveform Classification Based on a Stacked Convolutional and Bidirectional Long Short-Term Memory.

Siti Nurmaini, Annisa Darmawahyuni, Muhammad Naufal Rachmatullah, Jannes Effendi, Ade Iriani Sapitri, Firdaus, Bambang Tutuko

IEEE Access, 2021

2020

Accurate Detection of Septal Defects With Fetal Ultrasonography Images Using Deep Learning-Based Multiclass Instance Segmentation.

Siti Nurmaini, Muhammad Naufal Rachmatullah, Ade Iriani Sapitri, Annisa Darmawahyuni, Adithia Jovandy, Firdaus, Bambang Tutuko, Rossi Passarella

IEEE Access, 2020