Artificial intelligence in metabolomics: A current review

J Chi, J Shu, M Li, R Mudappathi, Y Jin, F Lewis… - TrAC Trends in …, 2024 - Elsevier
Metabolomics and artificial intelligence (AI) form a synergistic partnership. Metabolomics
generates large datasets comprising hundreds to thousands of metabolites with complex …

A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique

SS Fiyadh, SM Alardhi, M Al Omar, MM Aljumaily… - Heliyon, 2023 - cell.com
Water is the most necessary and significant element for all life on earth. Unfortunately, the
quality of the water resources is constantly declining as a result of population development …

Utilizing convolutional neural networks to classify monkeypox skin lesions

EHI Eliwa, AM El Koshiry, T Abd El-Hafeez… - Scientific reports, 2023 - nature.com
Monkeypox is a rare viral disease that can cause severe illness in humans, presenting with
skin lesions and rashes. However, accurately diagnosing monkeypox based on visual …

Optimizing epileptic seizure recognition performance with feature scaling and dropout layers

A Omar, T Abd El-Hafeez - Neural Computing and Applications, 2024 - Springer
Epilepsy is a widespread neurological disorder characterized by recurring seizures that
have a significant impact on individuals' lives. Accurately recognizing epileptic seizures is …

[HTML][HTML] Comparison of accuracy and reliability of random forest, support vector machine, artificial neural network and maximum likelihood method in land use/cover …

MS Chowdhury - Environmental Challenges, 2024 - Elsevier
Accurate land use and land cover (LULC) is crucial for sustainable urban planning and for
many scientific researches. However, the demand for accurate LULC maps is increasing; it …

Predicting the risk of hypertension using machine learning algorithms: A cross sectional study in Ethiopia

MM Islam, MJ Alam, M Maniruzzaman, NAMF Ahmed… - Plos one, 2023 - journals.plos.org
Background and objectives Hypertension (HTN), a major global health concern, is a leading
cause of cardiovascular disease, premature death and disability, worldwide. It is important to …

Integrated optical-thermal model and deep learning technique to estimate the performance of a conical cavity receiver coupled solar parabolic dish collector

A Rajan, KS Reddy - Energy Conversion and Management, 2024 - Elsevier
An integrated optical-thermal model was developed by adopting ray tracing using the Monte-
Carlo algorithm and Computational Fluid Dynamics (CFD) for evaluating the performance of …

Optimizing plant breeding programs for genomic selection

LF Merrick, AW Herr, KS Sandhu, DN Lozada… - Agronomy, 2022 - mdpi.com
Plant geneticists and breeders have used marker technology since the 1980s in quantitative
trait locus (QTL) identification. Marker-assisted selection is effective for large-effect QTL but …

[HTML][HTML] Random forest with feature selection and K-fold cross validation for predicting the electrical and thermal efficiencies of air based photovoltaic-thermal systems

B Elkari, Y Chaibi, T Kousksou - Energy Reports, 2024 - Elsevier
The recent global energy transition policies emphasize the utilization of renewable sources
as a primary energy solution. Solar energy systems, in particular, offer significant …

Novel GA-Based DNN Architecture for Identifying the Failure Mode with High Accuracy and Analyzing Its Effects on the System

N Rezaeian, R Gurina, OA Saltykova, L Hezla… - Applied Sciences, 2024 - mdpi.com
Symmetric data play an effective role in the risk assessment process, and, therefore,
integrating symmetrical information using Failure Mode and Effects Analysis (FMEA) is …