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Umeå universitet
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Huvudmenyn dold.

Paolo Soda

Kontakt

E-post
paolo.soda@umu.se
Telefon

Verksam vid

Anknytning
Gästprofessor vid Institutionen för strålningsvetenskaper
Plats
10c, Målpunkt E03, Norrlands universitetssjukhus Umeå universitet, 901 87 Umeå
Early Experiences on using Triplet Networks for Histological Subtype Classification in Non-Small Cell Lung Cancer
2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS): Proceedings, IEEE 2023 : 832-837
Aksu, Fatih; Gelardi, Fabrizia; Chiti, Arturo; et al.
3t-mri artificial intelligence in patients with invasive breast cancer to predict distant metastasis status: a pilot study
Cancers, MDPI 2023, Vol. 15, (1)
Calabrese, Alessandro; Santucci, Domiziana; Gravina, Michela; et al.
A comparative study between paired and unpaired image quality assessment in low-dose CT denoising
2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS): Proceedings, IEEE 2023 : 471-476
Di Feola, Francesco; Tronchin, Lorenzo; Soda, Paolo
Multi-objective optimization determines when, which and how to fuse deep networks: an application to predict COVID-19 outcomes
Computers in Biology and Medicine, Elsevier 2023, Vol. 154
Guarrasi, Valerio; Soda, Paolo
Stage I stereotactic body radiation therapy outcome's prediction models: perfection is the enemy of utility
Journal of Thoracic Oncology, Elsevier 2023, Vol. 18, (3) : 262-264
Ramella, Sara; Soda, Paolo
RadioPathomics: multimodal learning in non-small cell lung cancer for adaptive radiotherapy
IEEE Access, IEEE 2023, Vol. 11 : 47563-47578
Tortora, Matteo; Cordelli, Ermanno; Sicilia, Rosa; et al.
An empirical study on the joint impact of feature selection and data resampling on imbalance classification
Applied intelligence (Boston), Springer Nature 2023, Vol. 53 : 5449-5461
Zhang, Chongsheng; Soda, Paolo; Bi, Jingjun; et al.
A multimodal ensemble driven by multiobjective optimisation to predict overall survival in non-small-cell lung cancer
Journal of Imaging, MDPI 2022, Vol. 8, (11)
Caruso, Camillo Maria; Guarrasi, Valerio; Cordelli, Ermanno; et al.
Evaluating tumour bounding options for deep learning-based axillary lymph node metastasis prediction in breast cancer
2022 26th International Conference on Pattern Recognition (ICPR), Institute of Electrical and Electronics Engineers (IEEE) 2022 : 4335-4342
Gravina, Michela; Cordelli, Ermanno; Santucci, Domiziana; et al.
CNN-Based Approaches with Different Tumor Bounding Options for Lymph Node Status Prediction in Breast DCE-MRI
Cancers, MDPI 2022, Vol. 14, (19)
Santucci, Domiziana; Faiella, Eliodoro; Gravina, Michela; et al.
MLOps: A Taxonomy and a Methodology
IEEE Access, Institute of Electrical and Electronics Engineers (IEEE) 2022, Vol. 10 : 63606-63618
Testi, Matteo; Ballabio, Matteo; Frontoni, Emanuele; et al.
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