| Prediction of breast cancer, comparative review of machine learning techniques, and their analysis N Fatima, L Liu, S Hong, H Ahmed IEEE Access 8, 150360-150376, 2020 | 173 | 2020 |
| Human‐to‐Ai interrater agreement for lung ultrasound scoring in COVID‐19 Patients N Fatima, F Mento, A Zanforlin, A Smargiassi, E Torri, T Perrone, L Demi Journal of Ultrasound in Medicine 42 (4), 843-851, 2023 | 21 | 2023 |
| Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from covid-19 patients: From frame to prognostic-level U Khan, S Afrakhteh, F Mento, N Fatima, L De Rosa, LL Custode, Z Azam, ... Ultrasonics 132, 106994, 2023 | 15 | 2023 |
| Automatic scoring of covid-19 lus videos using cross-correlation-based features aggregated from frame-level confidence levels obtained by a pre-trained deep neural network S Afrakhteh, F Mento, U Khan, L De Rosa, N Fatima, Z Azam, F Tursi, ... 2022 IEEE International Ultrasonics Symposium (IUS), 1-3, 2022 | 2 | 2022 |
| Automatic segmentation of 2D echocardiography ultrasound images by means of generative adversarial network N Fatima, S Afrakhteh, G Iacca, L Demi IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2024 | | 2024 |
| Oversample minority classes in Lung Ultrasound using Generative Adversarial Network N Fatima, F Mento, L Demi 2023 IEEE International Ultrasonics Symposium (IUS), 1-3, 2023 | | 2023 |
| Synthetic lung ultrasound data generation using autoencoder with generative adversarial network N Fatima, R Inchingolo, A Smargiassi, G Soldati, E Torri, T Perrone, ... The Journal of the Acoustical Society of America 153 (3_supplement), A190-A190, 2023 | | 2023 |
