M
Muhammad Irfan
Researcher at Najran University
Publications - 928
Citations - 10675
Muhammad Irfan is an academic researcher from Najran University. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 36, co-authored 646 publications receiving 6333 citations. Previous affiliations of Muhammad Irfan include Pakistan Council of Scientific and Industrial Research & American University of Sharjah.
Papers
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Brain Tumor Detection and Classification Using Fine-Tuned CNN with ResNet50 and U-Net Model: A Study on TCGA-LGG and TCIA Dataset for MRI Applications
Abdullah A. Asiri,Ahmad Shaf,Tariq S. Abdul-Razaq and Faez H. Ali,Muhammad Aamir,Muhammad Irfan,Saeed Alqahtani,Khlood Mohammed Mehdar,Hanan Halawani,Abdullah F. Alshamrani,Samar M. Alqhtani +9 more
TL;DR: In this paper , an improved fine-tuned model based on CNN with ResNet50 and U-Net was proposed to solve the problem of detecting and classifying the brain tumor accurately at the initial stages to avoid maximum death loss.
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Hubungan Fasilitas Perpustakaan Sekolah dengan Minat Baca Siswa Kelas V SD Gugus 32 Kecamatan Citta
TL;DR: In this article , a quantitative study with a correlation design was conducted to determine the relationship between school library facilities and reading interest in fifth grade students of SD Gugus 32, Citta District, Soppeng Regency.
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Multi-region electricity demand prediction with ensemble deep neural networks
Muhammad Irfan,Ahmad Shaf,Tariq S. Abdul-Razaq and Faez H. Ali,Saifur Rahman,Salim Nasar Faraj Mursal,Faisal Althobiani,H. M. Attar +6 more
TL;DR: In this article , a deep-ensembled neural network was used to anticipate hourly power utilization, providing a clear and effective approach for predicting power consumption, and the proposed model effectively trained long-term dependencies in sequence order.
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Detection of heart valve function disorders with artificial neural network (ANN) algorithm
TL;DR: In this paper , an Artificial Neural Network (ANN) algorithm was used to detect abnormalities in the heart valves, by distinguishing normal heart sounds from abnormal heart sounds by employing a neural network.
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In Silico Characterization and Analysis of Clinically Significant Variants of Lipase-H (LIPH Gene) Protein Associated with Hypotrichosis
H. Khan,M. Ijaz,Metab Alharbi,Yasir Ali,Faisal Ahmad,Ramsha Azhar,Sajjad Ahmad,Muhammad Irfan,Abdul Aziz +8 more
TL;DR: In this article , a range of sequence and architecture-based bioinformatics techniques were used to identify potentially harmful nsSNPs of the Lipase-H (LIPH) gene.