A Modified Deep Residual-Convolutional Neural Network for Accurate Imputation of Missing Data
Handling missing data accurately is critical in clinical research, where data quality directly impacts decision-making and patient outcomes. While deep learning (DL) techniques for data imputation have gained attention, chall... | Find, read and cite all the research you need on Tech Science Press
Authors
- Akhiar Wista Arum
- Ade Iriani Sapitri (ORCID: https://orcid.org/0000-0003-4796-1901)
- Annisa Darmawahyuni (ORCID: https://orcid.org/0000-0002-0229-5717)
- Bambang Tutuko (ORCID: https://orcid.org/0000-0002-2051-8988)
- Muhammad Naufal Rachmatullah (ORCID: https://orcid.org/0000-0003-3553-3475)
- Anggun Islami (ORCID: https://orcid.org/0009-0001-3065-2873)
- Siti Nurmaini (ORCID: https://orcid.org/0000-0002-8024-2952)
- Firdaus Firdaus
- Muhammad Irfan Karim
- Yultrien Yultrien
- Ramadhana Noor Salassa Wandya
Institutions
- Sriwijaya University (ID)
Publication Details
- Journal
- Computers, materials & continua/Computers, materials & continua (Print)
- Published
- 2025-01-01
- DOI
- https://doi.org/10.32604/cmc.2024.055906
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universitas Sriwijaya