Research

Trustworthy AI for medical imaging, made rigorous.

My work asks a hard question: when can we trust what a model tells us? I build detection systems for mammography that quantify their own uncertainty, explain their decisions, and know when to abstain.

Uncertainty quantificationExplainable AI (XAI)Selective predictionBreast cancer CADTrustworthy medical imaging

Selected publications

Uncertainty Quantification for Trustworthy Breast Cancer CAD in Mammography: A Critical Review and Research Agenda

I. Ait Lbachir, I. Daoudi, R. Nassih

International Conference on Intelligent Systems and Digital Applications (ISDA), IEEE · 2026

Published

Digital Breast Tomosynthesis Reconstruction Techniques in Healthcare Systems: A Review

I. Samiry, I. Ait Lbachir, I. Daoudi, S. Tallal, S. Adil

International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO), Springer · 2023

Published

Automatic computer-aided diagnosis system for mass detection and classification in mammography

I. Ait Lbachir, I. Daoudi, S. Tallal

Multimedia Tools and Applications (vol. 80), Springer · 2021

Journal

Saliency-Based Microcalcification Clusters Segmentation in Mammography

I. Ait Lbachir, I. Daoudi, S. Tallal

International Journal of Scientific & Technology Research (vol. 10) · 2021

Journal

Automatic detection of suspicious lesions in mammograms by histogram-peak-analysis based K-means

I. Ait Lbachir, I. Daoudi, S. Tallal

International Symposium on Signal, Image, Video and Communications (ISIVC), IEEE · 2018

Published

A new mammogram preprocessing method for Computer-Aided Diagnosis systems

I. Ait Lbachir, R. Es-Salhi, I. Daoudi, S. Tallal

IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), IEEE · 2017

Published

A survey on segmentation techniques of mammogram images

I. Ait Lbachir, R. Es-salhi, I. Daoudi, S. Tallal, H. Medromi

International Symposium on Ubiquitous Networking, Springer · 2016

Published

A complete, up-to-date list lives on ORCID and Google Scholar.