[HTML][HTML] Explainable AI for operational research: A defining framework, methods, applications, and a research agenda

KW De Bock, K Coussement, A De Caigny… - European Journal of …, 2024 - Elsevier
The ability to understand and explain the outcomes of data analysis methods, with regard to
aiding decision-making, has become a critical requirement for many applications. For …

Towards effective clinical decision support systems: A systematic review

F Hak, T Guimarães, M Santos - PLoS One, 2022 - journals.plos.org
Background Clinical Decision Support Systems (CDSS) are used to assist the decision-
making process in the healthcare field. Develo** an effective CDSS is an arduous task …

Deep learning algorithm predicts diabetic retinopathy progression in individual patients

F Arcadu, F Benmansour, A Maunz, J Willis… - NPJ digital …, 2019 - nature.com
The global burden of diabetic retinopathy (DR) continues to worsen and DR remains a
leading cause of vision loss worldwide. Here, we describe an algorithm to predict DR …

A stacking-based ensemble learning method for earthquake casualty prediction

S Cui, Y Yin, D Wang, Z Li, Y Wang - Applied Soft Computing, 2021 - Elsevier
The estimation of the loss and prediction of the casualties in earthquake-stricken areas are
vital for making rapid and accurate decisions during rescue efforts. The number of casualties …

Early segmentation of students according to their academic performance: A predictive modelling approach

VL Miguéis, A Freitas, PJV Garcia, A Silva - Decision Support Systems, 2018 - Elsevier
The early classification of university students according to their potential academic
performance can be a useful strategy to mitigate failure, to promote the achievement of …

An improved random forest-based rule extraction method for breast cancer diagnosis

S Wang, Y Wang, D Wang, Y Yin, Y Wang, Y ** - Applied Soft Computing, 2020 - Elsevier
Breast cancer has been becoming the main cause of death in women all around the world.
An accurate and interpretable method is necessary for diagnosing patients with breast …

The analytics paradigm in business research

D Delen, HM Zolbanin - Journal of Business Research, 2018 - Elsevier
The availability of data in massive collections in recent past not only has enabled data-
driven decision-making, but also has created new questions that cannot be addressed …

A survey on multimodal data-driven smart healthcare systems: approaches and applications

Q Cai, H Wang, Z Li, X Liu - IEEE Access, 2019 - ieeexplore.ieee.org
Multimodal data-driven approach has emerged as an important driving force for smart
healthcare systems with applications ranging from disease analysis to triage, diagnosis and …

Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus

N Singh, P Singh - Biocybernetics and Biomedical Engineering, 2020 - Elsevier
Diabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated
blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of …

Synthesis of nickel-sphere coated Ni-Mn layer for efficient electrochemical detection of urea

N Ezzat, MA Hefnawy, SA Fadlallah, RM El-Sherif… - Scientific Reports, 2024 - nature.com
Using a trustworthy electrochemical sensor in the detection of urea in real blood samples
received a great attention these days. A thin layer of nickel-coated nickel-manganese (Ni …