Machine learning in medical applications: A review of state-of-the-art methods

M Shehab, L Abualigah, Q Shambour… - Computers in Biology …, 2022‏ - Elsevier
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

Machine learning and data mining in manufacturing

A Dogan, D Birant - Expert Systems with Applications, 2021‏ - Elsevier
Manufacturing organizations need to use different kinds of techniques and tools in order to
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …

Optimizing biodiesel production from waste with computational chemistry, machine learning and policy insights: a review

AI Osman, M Nasr, M Farghali, AK Rashwan… - Environmental …, 2024‏ - Springer
The excessive reliance on fossil fuels has resulted in an energy crisis, environmental
pollution, and health problems, calling for alternative fuels such as biodiesel. Here, we …

An optimal pruning algorithm of classifier ensembles: dynamic programming approach

OA Alzubi, JA Alzubi, M Alweshah, I Qiqieh… - Neural Computing and …, 2020‏ - Springer
In recent years, classifier ensemble techniques have drawn the attention of many
researchers in the machine learning research community. The ultimate goal of these …

[HTML][HTML] Post-hoc explanation of black-box classifiers using confident itemsets

M Moradi, M Samwald - Expert Systems with Applications, 2021‏ - Elsevier
Abstract Black-box Artificial Intelligence (AI) methods, eg deep neural networks, have been
widely utilized to build predictive models that can extract complex relationships in a dataset …

A hybrid feature selection with ensemble classification for imbalanced healthcare data: A case study for brain tumor diagnosis

S Huda, J Yearwood, HF Jelinek, MM Hassan… - IEEE …, 2016‏ - ieeexplore.ieee.org
Electronic health records (EHRs) are providing increased access to healthcare data that can
be made available for advanced data analysis. This can be used by the healthcare …

Lung nodules detection using semantic segmentation and classification with optimal features

T Meraj, HT Rauf, S Zahoor, A Hassan, MIU Lali… - Neural Computing and …, 2021‏ - Springer
Lung cancer is a deadly disease if not diagnosed in its early stages. However, early
detection of lung cancer is a challenging task due to the shape and size of its nodules …

[HTML][HTML] IntelliHealth: a medical decision support application using a novel weighted multi-layer classifier ensemble framework

S Bashir, U Qamar, FH Khan - Journal of biomedical informatics, 2016‏ - Elsevier
Accuracy plays a vital role in the medical field as it concerns with the life of an individual.
Extensive research has been conducted on disease classification and prediction using …

Identification of membrane protein types via multivariate information fusion with Hilbert–Schmidt independence criterion

H Wang, Y Ding, J Tang, F Guo - Neurocomputing, 2020‏ - Elsevier
Membrane proteins perform a variety of functions vital to the survival of organisms, such as
oxidoreductase, transferase or hydrolase. If the type of membrane protein can be detected …

Tracking and predicting technological knowledge interactions between artificial intelligence and wind power: Multimethod patent analysis

J Wang, L Cheng, L Feng, KY Lin, L Zhang… - Advanced Engineering …, 2023‏ - Elsevier
To track the dynamics of AI and wind power technology knowledge interaction and predict
future interaction directions, this study proposes a multiview and multilayer patent analysis …