| Combining weighted total variation and deep image prior for natural and medical image restoration via ADMM P Cascarano, A Sebastiani, MC Comes, G Franchini, F Porta 2021 21st international conference on computational science and its …, 2021 | 89* | 2021 |
| Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs MC Comes, A Fanizzi, S Bove, V Didonna, S Diotaiuti, D La Forgia, ... Scientific Reports 11 (1), 14123, 2021 | 72 | 2021 |
| Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments A Mencattini, D Di Giuseppe, MC Comes, P Casti, F Corsi, FR Bertani, ... Scientific reports 10 (1), 7653, 2020 | 66 | 2020 |
| Radiomic feature reduction approach to predict breast cancer by contrast-enhanced spectral mammography images R Massafra, S Bove, V Lorusso, A Biafora, MC Comes, V Didonna, ... Diagnostics 11 (4), 684, 2021 | 59 | 2021 |
| Early prediction of breast cancer recurrence for patients treated with neoadjuvant chemotherapy: a transfer learning approach on DCE-MRIs MC Comes, D La Forgia, V Didonna, A Fanizzi, F Giotta, A Latorre, ... Cancers 13 (10), 2298, 2021 | 52 | 2021 |
| The influence of spatial and temporal resolutions on the analysis of cell-cell interaction: a systematic study for time-lapse microscopy applications MC Comes, P Casti, A Mencattini, D Di Giuseppe, F Mermet-Meillon, ... Scientific reports 9 (1), 6789, 2019 | 47 | 2019 |
| A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients S Bove, MC Comes, V Lorusso, C Cristofaro, V Didonna, G Gatta, F Giotta, ... Scientific Reports 12 (1), 7914, 2022 | 40 | 2022 |
| Robustness evaluation of a deep learning model on sagittal and axial breast DCE-MRIs to predict pathological complete response to neoadjuvant chemotherapy R Massafra, MC Comes, S Bove, V Didonna, G Gatta, F Giotta, A Fanizzi, ... Journal of Personalized Medicine 12 (6), 953, 2022 | 37 | 2022 |
| Recursive deep prior video: a super resolution algorithm for time-lapse microscopy of organ-on-chip experiments P Cascarano, MC Comes, A Mencattini, MC Parrini, EL Piccolomini, ... Medical Image Analysis 72, 102124, 2021 | 35 | 2021 |
| Analyzing breast cancer invasive disease event classification through explainable artificial intelligence R Massafra, A Fanizzi, N Amoroso, S Bove, MC Comes, D Pomarico, ... Frontiers in Medicine 10, 1116354, 2023 | 34 | 2023 |
| Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response M D’Orazio, M Murdocca, A Mencattini, P Casti, J Filippi, G Antonelli, ... Scientific Reports 12 (1), 8545, 2022 | 34 | 2022 |
| Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence A Fanizzi, F Fadda, MC Comes, S Bove, A Catino, E Di Benedetto, ... Scientific Reports 13 (1), 20605, 2023 | 32 | 2023 |
| A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients MC Comes, L Fucci, F Mele, S Bove, C Cristofaro, I De Risi, A Fanizzi, ... Scientific Reports 12 (20366), 2022 | 32 | 2022 |
| Learning cancer-related drug efficacy exploiting consensus in coordinated motility within cell clusters D Di Giuseppe, F Corsi, A Mencattini, MC Comes, P Casti, C Di Natale, ... IEEE Transactions on Biomedical Engineering 66 (10), 2882-2888, 2019 | 28 | 2019 |
| Multi-scale generative adversarial network for improved evaluation of cell–cell interactions observed in organ-on-chip experiments MC Comes, J Filippi, A Mencattini, P Casti, G Cerrato, A Sauvat, ... Neural Computing and Applications 33 (8), 3671-3689, 2021 | 27 | 2021 |
| Deciphering cancer cell behavior from motility and shape features: Peer prediction and dynamic selection to support cancer diagnosis and therapy M D'Orazio, F Corsi, A Mencattini, D Di Giuseppe, M Colomba Comes, ... Frontiers in oncology 10, 580698, 2020 | 27 | 2020 |
| Machine learning microfluidic based platform: Integration of Lab-on-Chip devices and data analysis algorithms for red blood cell plasticity evaluation in Pyruvate Kinase … A Mencattini, V Rizzuto, G Antonelli, D Di Giuseppe, M D’Orazio, J Filippi, ... Sensors and Actuators A: Physical 351, 114187, 2023 | 24 | 2023 |
| Response predictivity to neoadjuvant therapies in breast cancer: a qualitative analysis of background parenchymal enhancement in DCE-MRI D La Forgia, A Vestito, M Lasciarrea, MC Comes, S Diotaiuti, F Giotta, ... Journal of Personalized Medicine 11 (4), 256, 2021 | 24 | 2021 |
| A CT-based transfer learning approach to predict NSCLC recurrence: The added-value of peritumoral region S Bove, A Fanizzi, F Fadda, MC Comes, A Catino, A Cirillo, C Cristofaro, ... PLoS One 18 (5), e0285188, 2023 | 20 | 2023 |
| Pathological complete response to neoadjuvant chemoimmunotherapy for early triple-negative breast cancer: an updated meta-analysis A Rizzo, A Cusmai, R Massafra, S Bove, MC Comes, A Fanizzi, L Rinaldi, ... Cells 11 (12), 1857, 2022 | 20 | 2022 |
Samantha BoveIRCCS Istituto Tumori 'Giovanni Paolo II' - Bari, IltalyVerified email at studenti.uniba.it
