Muhammad Naufal Rachmatullah

Orcid: 0000-0003-3553-3475

According to our database1, Muhammad Naufal Rachmatullah authored at least 16 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Health-Related Data Analysis Using Metaheuristic Optimization and Machine Learning.
IEEE Access, 2024

2023
Improved delineation model of a standard 12-lead electrocardiogram based on a deep learning algorithm.
BMC Medical Informatics Decis. Mak., December, 2023

Accurate Fetal QRS-Complex Classification from Abdominal Electrocardiogram Using Deep Learning.
Int. J. Comput. Intell. Syst., December, 2023

Automatic echocardiographic anomalies interpretation using a stacked residual-dense network model.
BMC Bioinform., December, 2023

CervicoXNet: an automated cervicogram interpretation network.
Medical Biol. Eng. Comput., September, 2023

Empowering AI-Diagnosis: Deep Learning Abilities for Accurate Atrial Fibrillation Classification.
Int. J. Online Biomed. Eng., 2023

2022
Short Single-Lead ECG Signal Delineation-Based Deep Learning: Implementation in Automatic Atrial Fibrillation Identification.
Sensors, 2022

Automated Precancerous Lesion Screening Using an Instance Segmentation Technique for Improving Accuracy.
Sensors, 2022

Deep learning-based electrocardiogram rhythm and beat features for heart abnormality classification.
PeerJ Comput. Sci., 2022

An improved semantic segmentation with region proposal network for cardiac defect interpretation.
Neural Comput. Appl., 2022

2021
Deep Learning-Based Computer-Aided Fetal Echocardiography: Application to Heart Standard View Segmentation for Congenital Heart Defects Detection.
Sensors, 2021

AFibNet: an implementation of atrial fibrillation detection with convolutional neural network.
BMC Medical Informatics Decis. Mak., 2021

Beat-to-Beat Electrocardiogram Waveform Classification Based on a Stacked Convolutional and Bidirectional Long Short-Term Memory.
IEEE Access, 2021

2020
Robust detection of atrial fibrillation from short-term electrocardiogram using convolutional neural networks.
Future Gener. Comput. Syst., 2020

Accurate Detection of Septal Defects With Fetal Ultrasonography Images Using Deep Learning-Based Multiclass Instance Segmentation.
IEEE Access, 2020

2019
Deep Learning with a Recurrent Network Structure in the Sequence Modeling of Imbalanced Data for ECG-Rhythm Classifier.
Algorithms, 2019


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