A systematic review of explainable artificial intelligence in terms of different application domains and tasks

MR Islam, MU Ahmed, S Barua, S Begum - Applied Sciences, 2022 - mdpi.com
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved
and are now being employed in almost every application domain to develop automated or …

A survey on artificial intelligence (ai) and explainable ai in air traffic management: Current trends and development with future research trajectory

A Degas, MR Islam, C Hurter, S Barua, H Rahman… - Applied Sciences, 2022 - mdpi.com
Air Traffic Management (ATM) will be more complex in the coming decades due to the
growth and increased complexity of aviation and has to be improved in order to maintain …

[HTML][HTML] SurvSHAP (t): time-dependent explanations of machine learning survival models

M Krzyziński, M Spytek, H Baniecki, P Biecek - Knowledge-Based Systems, 2023 - Elsevier
Abstract Machine and deep learning survival models demonstrate similar or even improved
time-to-event prediction capabilities compared to classical statistical learning methods yet …

Overview of explainable artificial intelligence for prognostic and health management of industrial assets based on preferred reporting items for systematic reviews and …

AKM Nor, SR Pedapati, M Muhammad, V Leiva - Sensors, 2021 - mdpi.com
Surveys on explainable artificial intelligence (XAI) are related to biology, clinical trials,
fintech management, medicine, neurorobotics, and psychology, among others. Prognostics …

[HTML][HTML] Daily soil moisture map** at 1 km resolution based on SMAP data for desertification areas in northern China

P Rao, Y Wang, F Wang, Y Liu… - Earth System Science …, 2022 - essd.copernicus.org
Land surface soil moisture (SM) plays a critical role in hydrological processes and terrestrial
ecosystems in desertification areas. Passive microwave remote-sensing products such as …

Continuous fixed-bed column adsorption of perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) from canal water using zero-valent Iron-based …

D Ordonez, A Podder, A Valencia… - Separation and …, 2022 - Elsevier
Per-and polyfluoroalkyl substances (PFAS) belong to a class of anthropogenic chemicals
that were popularly used by industry for their hydrophobicity and stain resistance; yet the …

Identifying marine food web homogenization patterns

Y Xu, X Huo, F Jordán, M Zhou, Y Cai… - Frontiers in Marine …, 2023 - frontiersin.org
Ecosystems become increasingly similar to each other, based on species composition.
Despite the inevitability of homogenized ecosystems due to global change, few studies have …

Counterfactual explanation of machine learning survival models

M Kovalev, L Utkin, F Coolen, A Konstantinov - Informatica, 2021 - content.iospress.com
A method for counterfactual explanation of machine learning survival models is proposed.
One of the difficulties of solving the counterfactual explanation problem is that the classes of …

SurvBeX: an explanation method of the machine learning survival models based on the Beran estimator

LV Utkin, DY Eremenko, AV Konstantinov - International Journal of Data …, 2024 - Springer
An explanation method called SurvBeX is proposed to interpret predictions of the machine
learning survival black-box models. The main idea behind the method is to use the modified …

Wasserstein-based fairness interpretability framework for machine learning models

A Miroshnikov, K Kotsiopoulos, R Franks… - Machine Learning, 2022 - Springer
The objective of this article is to introduce a fairness interpretability framework for measuring
and explaining the bias in classification and regression models at the level of a distribution …