Amel Mhamdi's research presented at the 14th International Conference on Computational Collective Intelligence
Her article "Approximation of the sparse semi-negative matrix factorization for X-Ray covid-19 image classification", co-authored with researchers from the health-crisis-stricken University of Tunisia, has been selected for the 14th International Conference on Computational Collective Intelligence, to be held in Hammamet, Tunisia, from September 28 to 30.
Amel Mhamdi, is developing an analysis of the digital data generated by intensively used medical imaging to help radiologists make the right diagnosis of COVID-19 disease, by proposing a new semi-NMF (non-negative matrix) algorithm to detect COVID-19 patients on the basis of chest X-ray images.
This small team of researchers is delighted to retain its mathematical logic and continue to work towards responsible AI.