Explainable artificial intelligence for drug discovery and development-a comprehensive survey
The field of drug discovery has experienced a remarkable transformation with the advent of
artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI and …
artificial intelligence (AI) and machine learning (ML) technologies. However, as these AI and …
Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture
LP Joseph, EA Joseph, R Prasad - Computers in Biology and Medicine, 2022 - Elsevier
Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …
Early prediction of diabetes using an ensemble of machine learning models
Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of
significant complications, including cardiovascular disease, kidney failure, diabetic …
significant complications, including cardiovascular disease, kidney failure, diabetic …
Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
VG Nguyen, P Sharma, Ü Ağbulut… - Biofuels, Bioproducts …, 2024 - Wiley Online Library
Biochar is emerging as a potential solution for biomass conversion to meet the ever
increasing demand for sustainable energy. Efficient management systems are needed in …
increasing demand for sustainable energy. Efficient management systems are needed in …
Potential of explainable artificial intelligence in advancing renewable energy: challenges and prospects
VN Nguyen, W Tarełko, P Sharma, AS El-Shafay… - Energy & …, 2024 - ACS Publications
Modern machine learning (ML) techniques are making inroads in every aspect of renewable
energy for optimization and model prediction. The effective utilization of ML techniques for …
energy for optimization and model prediction. The effective utilization of ML techniques for …
[HTML][HTML] Enhanced joint hybrid deep neural network explainable artificial intelligence model for 1-hr ahead solar ultraviolet index prediction
Abstract Background and Objective Exposure to solar ultraviolet (UV) radiation can cause
malignant keratinocyte cancer and eye disease. Develo** a user-friendly, portable, real …
malignant keratinocyte cancer and eye disease. Develo** a user-friendly, portable, real …
Advances in Henry Gas Solubility Optimization: A Physics-Inspired Metaheuristic Algorithm With Its Variants and Applications
MA El-Shorbagy, A Bouaouda, HA Nabwey… - IEEE …, 2024 - ieeexplore.ieee.org
The Henry Gas Solubility Optimization (HGSO) is a physics-based metaheuristic inspired by
Henry's law, which describes the solubility of the gas in a liquid under specific pressure …
Henry's law, which describes the solubility of the gas in a liquid under specific pressure …
Development of a smartphone-based expert system for COVID-19 risk prediction at early stage
COVID-19 has imposed many challenges and barriers on traditional healthcare systems due
to the high risk of being infected by the coronavirus. Modern electronic devices like …
to the high risk of being infected by the coronavirus. Modern electronic devices like …
New criteria for wrapper feature selection to enhance bearing fault classification
Classification is a critical task in many fields, including signal processing and data analysis.
The accuracy and stability of classification results can be improved by selecting the most …
The accuracy and stability of classification results can be improved by selecting the most …
Use of feature importance statistics to accurately predict asthma attacks using machine learning: A cross-sectional cohort study of the US population
AA Huang, SY Huang - Plos one, 2023 - journals.plos.org
Background Asthma attacks are a major cause of morbidity and mortality in vulnerable
populations, and identification of associations with asthma attacks is necessary to improve …
populations, and identification of associations with asthma attacks is necessary to improve …