A comprehensive review of artificial intelligence approaches in omics data processing: evaluating progress and challenges
AM Ali, MA Mohammed - International Journal of Mathematics, Statistics …, 2024 - ijmscs.org
The primary objective of this study is to review and assess the best available research on
omics-related artificial intelligence (AI) methods. Furthermore, it seeks to demonstrate the …
omics-related artificial intelligence (AI) methods. Furthermore, it seeks to demonstrate the …
Overview of big data analytics in modern astronomy
M Faaique - International Journal of Mathematics, Statistics, and …, 2024 - ijmscs.org
Astronomers are increasingly compelled to chart the universe with ever greater precision.
Projects like the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and the Large Synoptic …
Projects like the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and the Large Synoptic …
D2LFS2Net: Multi‐class skin lesion diagnosis using deep learning and variance‐controlled Marine Predator optimisation: An application for precision medicine
In computer vision applications like surveillance and remote sensing, to mention a few, deep
learning has had considerable success. Medical imaging still faces a number of difficulties …
learning has had considerable success. Medical imaging still faces a number of difficulties …
Federated auto-encoder and XGBoost schemes for multi-omics cancer detection in distributed fog computing paradigm
MA Mohammed, A Lakhan, KH Abdulkareem… - Chemometrics and …, 2023 - Elsevier
The digital healthcare paradigm has significantly improved based on distributed fog and
cloud networks for cancer detection with multiple classes in recent years. The paradigm …
cloud networks for cancer detection with multiple classes in recent years. The paradigm …
Applications and techniques of machine learning in cancer classification: A systematic review
The domain of Machine learning has experienced Substantial advancement and
development. Recently, showcasing a Broad spectrum of uses like Computational …
development. Recently, showcasing a Broad spectrum of uses like Computational …
Two-and-a-half order score-based model for solving 3D ill-posed inverse problems
Abstract Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are crucial
technologies in the field of medical imaging. Score-based models demonstrated …
technologies in the field of medical imaging. Score-based models demonstrated …
Rise of deep learning clinical applications and challenges in omics data: a systematic review
MA Mohammed, KH Abdulkareem, AM Dinar… - Diagnostics, 2023 - mdpi.com
This research aims to review and evaluate the most relevant scientific studies about deep
learning (DL) models in the omics field. It also aims to realize the potential of DL techniques …
learning (DL) models in the omics field. It also aims to realize the potential of DL techniques …
Lung cancer diagnosis based on weighted convolutional neural network using gene data expression
Lung cancer is thought to be a genetic disease with a variety of unknown origins.
Globocan2020 report tells in 2020 new cancer cases identified was 19.3 million and nearly …
Globocan2020 report tells in 2020 new cancer cases identified was 19.3 million and nearly …
Determination of bandgap of period 3, 4, and 5 transition metal dopants on zinc oxide using an artificial neural network based approach
Artificial intelligence (AI) and machine learning (ML) have rapidly emerged as valuable tools
for chemical research, offering new ways to analyze and understand complex chemical …
for chemical research, offering new ways to analyze and understand complex chemical …
[HTML][HTML] Towards Safe and Sustainable Reinforcement Learning for Real-Time Strategy Games
Abstract Combining Deep Neural Networks with Reinforcement Learning, known as Deep
Reinforcement Learning (DRL), is revolutionizing fields like medicine, industry, and gaming …
Reinforcement Learning (DRL), is revolutionizing fields like medicine, industry, and gaming …