Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991–2020)

R Alizadehsani, M Roshanzamir, S Hussain… - Annals of Operations …, 2021 - Springer
Understanding the data and reaching accurate conclusions are of paramount importance in
the present era of big data. Machine learning and probability theory methods have been …

Application of machine learning methods in fault detection and classification of power transmission lines: a survey

FM Shakiba, SM Azizi, M Zhou, A Abusorrah - Artificial Intelligence Review, 2023 - Springer
The rising development of power systems and smart grids calls for advanced fault diagnosis
techniques to prevent undesired interruptions and expenses. One of the most important part …

[HTML][HTML] Comparative analysis of RSM, ANN and ANFIS and the mechanistic modeling in eriochrome black-T dye adsorption using modified clay

CE Onu, JT Nwabanne, PE Ohale, CO Asadu - South African Journal of …, 2021 - Elsevier
The application of artificial neural network (ANN), response surface methodology (RSM),
and adaptive neuro-fuzzy inference system (ANFIS) in modeling the uptake of Eriochrome …

A survey of human gait-based artificial intelligence applications

EJ Harris, IH Khoo, E Demircan - Frontiers in Robotics and AI, 2022 - frontiersin.org
We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …

Multi-characteristic optimization and modeling analysis of electrocoagulation treatment of abattoir wastewater using iron electrode pairs

CC Obi, JT Nwabanne, CA Igwegbe, PE Ohale… - Journal of Water …, 2022 - Elsevier
Multi-characteristic optimization and modeling analysis of electrocoagulation (EC) treatment
of abattoir wastewater (AWW) using iron‑iron electrodes are reported. Response Surface …

Numerical evaluation of the upright columns with partial reinforcement along with the utilisation of neural networks with combining feature-selection method to predict …

E Taheri, P Mehrabi, S Rafiei, B Samali - Applied Sciences, 2021 - mdpi.com
This study evaluated the axial capacity of cold-formed racking upright sections strengthened
with an innovative reinforcement method by finite element modelling and artificial …

Clinical decision support system to predict chronic kidney disease: A fuzzy expert system approach

F Hamedan, A Orooji, H Sanadgol… - International journal of …, 2020 - Elsevier
Background and objectives Diagnosis and early intervention of chronic kidney disease are
essential to prevent loss of kidney function and a large amount of financial resources. To this …

Prediction of chronic kidney disease and its progression by artificial intelligence algorithms

FP Schena, VW Anelli, DI Abbrescia, T Di Noia - Journal of Nephrology, 2022 - Springer
Background and objective Aim of nephrologists is to delay the outcome and reduce the
number of patients undergoing renal failure (RF) by applying prevention protocols and …

[HTML][HTML] Taxonomy of hybrid architectures involving rule-based reasoning and machine learning in clinical decision systems: A scoping review

S Kierner, J Kucharski, Z Kierner - Journal of Biomedical Informatics, 2023 - Elsevier
Background As the application of Artificial Intelligence (AI) technologies increases in the
healthcare sector, the industry faces a need to combine medical knowledge, often …

RSM, ANN and ANFIS applications in modeling fermentable sugar production from enzymatic hydrolysis of Colocynthis Vulgaris Shrad seeds shell

CN Igwilo, NC Ude, IM Onoh, CB Enekwe… - Bioresource Technology …, 2022 - Elsevier
The artificial neural network (ANN), response surface methodology (RSM), and adaptive
neuro-fuzzy inference system (ANFIS) were applied to predict the yield of fermentable sugar …