Paolo Soda

0000-0003-2621-072X

Kontakt

paolo.soda@umu.se

Verksam vid

Gästprofessor vid Institutionen för diagnostik och intervention

5A, Målpunkt H62, Norrlands universitetssjukhus Umeå universitet, 901 85 Umeå

Publikationer Publikationer

Virtual scanner: leveraging resilient generative ai for radiological imaging in the era of medical digital twins

Ital-IA 2024 Thematic Workshops: Proceedings of the Ital-IA Intelligenza Artificiale - Thematic Workshopsco-located with the 4th CINI National Lab AIIS Conference on Artificial Intelligence (Ital-IA 2024), CEUR-WS 2024 : 60-65

Adornato, Carolina; Assolito, Cecilia; Cordelli, Ermanno; et al.

Towards AI-driven next generation personalized healthcare and well-being

Ital-IA 2024 Thematic Workshops: roceedings of the Ital-IA Intelligenza Artificiale - Thematic Workshopsco-located with the 4th CINI National Lab AIIS Conference on Artificial Intelligence (Ital-IA 2024), CEUR-WS 2024 : 360-365

Aksu, Fatih; Bria, Alessandro; Caragliano, Alice Natalina; et al.

A deep learning approach for overall survival prediction in lung cancer with missing values

Computer Methods and Programs in Biomedicine, Elsevier 2024, Vol. 254

Caruso, Camillo Maria; Guarrasi, Valerio; Ramella, Sara; et al.

AI-based methodologies for exoskeleton-assisted rehabilitation of the lower limb: a review

Frontiers in Robotics and AI, Frontiers Media S.A. 2024, Vol. 11

Coser, Omar; Tamantini, Christian; Soda, Paolo; et al.

Multi input–Multi output 3D CNN for dementia severity assessment with incomplete multimodal data

Artificial Intelligence in Medicine, Elsevier 2024, Vol. 149

Gravina, Michela; García-Pedrero, Angel; Gonzalo-Martín, Consuelo; et al.

Cross-modality calibration in multi-input network for axillary lymph node metastasis evaluation

IEEE Transactions on Artificial Intelligence, Institute of Electrical and Electronics Engineers (IEEE) 2024, Vol. 5, (9) : 4823-4836

Gravina, Michela; Santucci, Domiziana; Cordelli, Ermanno; et al.

Multimodal explainability via latent shift applied to COVID-19 stratification

Pattern Recognition, Elsevier 2024, Vol. 156

Guarrasi, Valerio; Tronchin, Lorenzo; Albano, Domenico; et al.

Emerging microorganisms and infectious diseases: one health approach for health shared vision

Genes, MDPI 2024, Vol. 15, (7)

Ristori, Maria Vittoria; Guarrasi, Valerio; Soda, Paolo; et al.

A deep learning approach for virtual contrast enhancement in Contrast Enhanced Spectral Mammography

Computerized Medical Imaging and Graphics, Elsevier 2024, Vol. 116

Rofena, Aurora; Guarrasi, Valerio; Sarli, Marina; et al.

Translating image XAI to multivariate time series

IEEE Access, IEEE 2024, Vol. 12 : 27484-27500

Tronchin, Lorenzo; Cordelli, Ermanno; Celsi, Lorenzo Ricciardi; et al.

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

Exploring early stress detection from multimodal time series with deep reinforcement learning

Proceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023, Institute of Electrical and Electronics Engineers (IEEE) 2023 : 1917-1920

Furia, Leonardo; Tortora, Matteo; Soda, Paolo; et al.

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

Building an AI-enabled metaverse for intelligent healthcare: opportunities and challenges

Proceedings of the Italia intelligenza artificiale: thematic workshops, CEUR-WS 2023 : 134-139

Guarrasi, Valerio; Tronchin, Lorenzo; Caruso, Camillo Maria; et al.

Deep pathomics: a new image-based tool for predicting response to treatment in stage III non-small cell lung cancer

PLOS ONE, Public Library of Science (PLoS) 2023, Vol. 18, (11)

Nibid, Lorenzo; Greco, Carlo; Cordelli, Ermanno; et al.

Named entity recognition in Italian lung cancer clinical reports using transformers

Proceedings - 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023, Institute of Electrical and Electronics Engineers (IEEE) 2023 : 4101-4107

Paolo, Domenico; Bria, Alessandro; Greco, Carlo; et al.

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)