Ahmed M. Salih

According to our database, Ahmed M. Salih authored at least 14 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

The Marriage of Neurotechnologies and Artificial Intelligence: Ethical, regulatory, and technological aspects.

Carlo Chiurco, Andrea Favaro, Silvia Francesca Storti, Lorenza Brusini, Ahmed M. Salih, Ilaria Boscolo Galazzo, Sergey M. Plis, Gloria Menegaz

IEEE Signal Process. Mag., September, 2025

Re-Visiting Explainable AI Evaluation Metrics to Identify The Most Informative Features.

Ahmed M. Salih

CoRR, February, 2025

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME.

Ahmed M. Salih, Zahra Raisi-Estabragh, Ilaria Boscolo Galazzo, Petia Radeva, Steffen E. Petersen, Karim Lekadir, Gloria Menegaz

Adv. Intell. Syst., January, 2025

2024

Characterizing the Contribution of Dependent Features in XAI Methods.

Ahmed M. Salih, Ilaria Boscolo Galazzo, Zahra Raisi-Estabragh, Steffen E. Petersen, Gloria Menegaz, Petia Radeva

IEEE J. Biomed. Health Informatics, November, 2024

A review of evaluation approaches for explainable AI with applications in cardiology.

Ahmed M. Salih, Ilaria Boscolo Galazzo, Polyxeni Gkontra, Elisa Rauseo, Aaron M. Lee, Karim Lekadir, Petia Radeva, Steffen E. Petersen, Gloria Menegaz

Artif. Intell. Rev., September, 2024

Common Steps in Machine Learning Might Hinder The Explainability Aims in Medicine.

Ahmed M. Salih

CoRR, 2024

Are Linear Regression Models White Box and Interpretable?

Ahmed M. Salih, Yuhe Wang

CoRR, 2024

Explainable Artificial Intelligence and Multicollinearity : A Mini Review of Current Approaches.

Ahmed M. Salih

CoRR, 2024

Explainable Artificial Intelligence for Dependent Features: Additive Effects of Collinearity.

Ahmed M. Salih

Proceedings of the 8th International Conference on Advances in Artificial Intelligence, 2024

2023

Commentary on explainable artificial intelligence methods: SHAP and LIME.

Ahmed M. Salih, Zahra Raisi-Estabragh, Ilaria Boscolo Galazzo, Petia Radeva, Steffen E. Petersen, Gloria Menegaz, Karim Lekadir

CoRR, 2023

2022

Explainable Artificial Intelligence for Magnetic Resonance Imaging Aging Brainprints: Grounds and challenges.

Ilaria Boscolo Galazzo, Federica Cruciani, Lorenza Brusini, Ahmed M. Salih, Petia Radeva, Silvia Francesca Storti, Gloria Menegaz

IEEE Signal Process. Mag., 2022

Investigating Explainable Artificial Intelligence for MRI-based Classification of Dementia: a New Stability Criterion for Explainable Methods.

Ahmed M. Salih, Ilaria Boscolo Galazzo, Federica Cruciani, Lorenza Brusini, Petia Radeva

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

A new scheme for the assessment of the robustness of Explainable Methods Applied to Brain Age estimation.

Ahmed M. Salih, Ilaria Boscolo Galazzo, Zahra Raisi-Estabragh, Steffen E. Petersen, Polyxeni Gkontra, Karim Lekadir, Gloria Menegaz, Petia Radeva

Proceedings of the 34th IEEE International Symposium on Computer-Based Medical Systems, 2021

2020

Microstructural Modulations in the Hippocampus Allow to Characterizing Relapsing-Remitting Versus Primary Progressive Multiple Sclerosis.

Lorenza Brusini, Ilaria Boscolo Galazzo, Muge Akinci, Federica Cruciani, Marco Pitteri, Stefano Ziccardi, Albulena Bajrami, Marco Castellaro, Ahmed M. Salih, Francesca B. Pizzini, Jorge Jovicich, Massimiliano Calabrese, Gloria Menegaz

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020