2025
Aresta, S., Nemni, R., Zanardo, M., Sirabian, G., Capelli, D., Alì, M., Vitali, P., Bertoldo, E. G., Fiolo, V., Bonanno, L., Maresca, G., Battista, P., Sardanelli, F., Pizzini, F. B., Castiglioni, I., & Salvatore, C. (2025). AI-based staging, causal hypothesis and progression of subjects at risk of Alzheimer's disease: A multicenter study. Frontiers in Neurology, 16, 1568086. https://doi.org/10.3389/fneur.2025.1568086
2024
Cordelli, E., Soda, P., Citter, S., Schiavon, E., Salvatore, C., Fazzini, D., Clementi, G., Cellina, M., Cozzi, A., Bortolotto, C., Preda, L., Francini, L., Tortora, M., Castiglioni, I., Papa, S., Sona, D., & Alì, M. (2024). Machine learning predicts pulmonary Long Covid sequelae using clinical data. BMC Medical Informatics and Decision Making, 24, Article 359. https://doi.org/10.1186/s12911-024-02745-3
Crimì, F., D’Alessandro, C., Zanon, C., Celotto, F., Salvatore, C., Interlenghi, M., Castiglioni, I., & Quaia, E. (2024). A machine learning model based on MRI radiomics to predict response to chemoradiation among patients with rectal cancer. Life, 14(12), 1530. https://doi.org/10.3390/life14121530
Palmirotta, C., Aresta, S., Battista, P., Tagliente, S., Lagravinese, G., Mongelli, D., Gelao, C., Fiore, P., Castiglioni, I., Minafra, B., & Salvatore, C. (2024). Unveiling the Diagnostic Potential of Linguistic Markers in Identifying Individuals with Parkinson’s Disease through Artificial Intelligence: A Systematic Review. Brain Sciences, 14(2), 137.
Alì, M., Salvatore, C., Interlenghi, M., Venturi, A., Colarieti, A., Fazzini, D., Papa, S., & Castiglioni, I. (2024). Optimization of PSA density threshold through automated prostate volume segmentation with deep learning for the diagnosis of clinically significant prostate cancer. Anticancer Research, 44(10), 5001–5007.
Alì, M., Salvatore, C., Interlenghi, M., Venturi, A., Colarieti, A., Fazzini, D., Papa, S., & Castiglioni, I. (2024). Optimization of PSA density threshold through automated prostate volume segmentation with deep learning for the diagnosis of clinically significant prostate cancer. Anticancer Research, 44(10), 5001–5007.
Cava, C., Sabetian, S., Salvatore, C., & Castiglioni, I. (2024). Pan-cancer classification of multi-omics data based on machine learning models. Network Modeling Analysis in Health Informatics and Bioinformatics, 13(1), 6.
Gitto, S., Annovazzi, A., Nulle, K., Interlenghi, M., Salvatore, C., Anelli, V., Baldi, J., Messina, C., Albano, D., Di Luca, F., & others (2024). X-rays radiomics-based machine learning classification of atypical cartilaginous tumour and high-grade chondrosarcoma of long bones. EBioMedicine, 101.
Chiappa, V., Interlenghi, M., Bascio, L., Fruscio, R., Salvatore, C., Ferrero, S., Rosati, F., Ficarelli, S., De Meis, L., Rolla, M., & others. (2024). 1311 Adnexal masses and risk of malignancy by radiomics, external validation of a decision support tool.
Salvatore, C., Nelli, V., Interlenghi, M., Fazzini, D., Alì, M., Magni, V., Papa, S., Sardanelli, F., Castiglioni, I., & others. (2024). A DL algorithm with optimized cost function for classification of malignant versus benign calcifications in mammograms.
Salvatore, C., Interlenghi, M., Schiavon, E., Lad, A., Fazzini, D., Alì, M., Papa, S., Sardanelli, F., Castiglioni, I., & others. (2024). Real-world performance of a PACS and mammography unit-vendor neutral DL system to classify breast density on mammograms and synthetic DBT views.
Gitto, S., Annovazzi, A., Nulle, K., Interlenghi, M., Salvatore, C., Anelli, V., Baldi, J., Messina, C., Albano, D., Di Luca, F., & others (2024). X-rays radiomics-based machine learning classification of atypical cartilaginous tumour and high-grade chondrosarcoma of long bones. EBioMedicine, 101.
Chiappa, V., Interlenghi, M., Bascio, L., Fruscio, R., Salvatore, C., Ferrero, S., Rosati, F., Ficarelli, S., De Meis, L., Rolla, M., & others. (2024). 1311 Adnexal masses and risk of malignancy by radiomics, external validation of a decision support tool.
Salvatore, C., Nelli, V., Interlenghi, M., Fazzini, D., Alì, M., Magni, V., Papa, S., Sardanelli, F., Castiglioni, I., & others. (2024). A DL algorithm with optimized cost function for classification of malignant versus benign calcifications in mammograms.
Salvatore, C., Interlenghi, M., Schiavon, E., Lad, A., Fazzini, D., Alì, M., Papa, S., Sardanelli, F., Castiglioni, I., & others. (2024). Real-world performance of a PACS and mammography unit-vendor neutral DL system to classify breast density on mammograms and synthetic DBT views.
Crimì, F., D’Alessandro, C., Salvatore, C., Castiglioni, I., & Spolverato, G. (2024). A machine learning model to predict response to chemoradiation among patients with rectal cancer. Journal of the American College of Surgeons, 239(5), S80.
Salvatore, C., Fazzini, D., Alì, M., Papa, S., Sardanelli, F., & Castiglioni, I. (2024, June). CO-17/16 Prestazioni in situ di un sistema DL integrato a PACS e unità mammografiche vendor neutral per classificare la densità mammaria in mammografie e DBT sintetiche. Poster presented at the 51st National Congress of the Italian Society of Medical and Interventional Radiology (SIRM), Milan, Italy.
2023
Albano, D., Gitto, S., Messina, C., Serpi, F., Salvatore, C., Castiglioni, I., Zagra, L., De Vecchi, E., & Sconfienza, L. (2023). MRI-based artificial intelligence to predict infection following total hip arthroplasty failure. La radiologia medica, 128(3), 340–346.
Gargano, M., Interlenghi, M., Cavaleri, T., Salvatore, C., Ludwig, N., & Castiglioni, I. (2023). Giovanna Garzoni Miniaturist at the Savoy Court: Imaging and Materials Investigations to Discover the Painting Technique. Applied Sciences, 13(5), 2790.
Gitto, S., Interlenghi, M., Cuocolo, R., Salvatore, C., Giannetta, V., Badalyan, J., Gallazzi, E., Spinelli, M., Gallazzi, M., Serpi, F., & others (2023). MRI radiomics-based machine learning for classification of deep-seated lipoma and atypical lipomatous tumor of the extremities. La radiologia medica, 128(8), 989–998.
Cava, C., Salvatore, C., & Castiglioni, I. (2023). Pan-cancer classification of gene expression data based on artificial neural network model. Applied Sciences, 13(13), 7355.
Battista, P., Nemni, R., Vitali, P., Alì, M., Zanardo, M., Salvatore, C., Sirabian, G., Capelli, D., Bet, L., Callus, E., & others (2023). ALZHEIMER’S DEMENTIA EARLY DIAGNOSIS, CHARACTERIZATION, PROGNOSIS AND TREATMENT DECISION VIA A SOFTWARE-AS-MEDICAL DEVICE WITH AN ARTIFICIAL INTELLIGENT AGENT. Alzheimer's & Dementia, 19, e075674.
Interlenghi, M., Sborgia, G., Venturi, A., Sardone, R., Pastore, V., Boscia, G., Landini, L., Scotti, G., Niro, A., Moscara, F., & others (2023). A Radiomic-based machine learning system to diagnose age-related macular degeneration from ultra-Widefield fundus Retinography. Diagnostics, 13(18), 2965.
Bruschetta, R., Campisi, S., Mastrogiuseppe, M., Leonardi, E., Aiello, S., Salvatore, C., Venturi, A., Schiavon, E., Campisi, A., Fam\`a, F., & others (2023). A deep learning approach for automatic video coding of deictic gestures in children with autism. In 2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) (pp. 1–6).
Chiappa, V., Interlenghi, M., Bascio, L., Salvatore, C., Fruscio, R., Ferrero, S., Rosati, F., De Meis, L., Rolla, M., Ficarelli, S., & others (2023). OC03. 03: Adnexal masses and risk of malignancy by radiomics: the future is now. Ultrasound in Obstetrics & Gynecology, 62, 7–7.
Chiappa, V., Bogani, G., Interlenghi, M., Vittori Antisari, G., Salvatore, C., Zanchi, L., Ludovisi, M., Leone Roberti Maggiore, U., Calareso, G., Haeusler, E., & others (2023). Using radiomics and machine learning applied to MRI to predict response to neoadjuvant chemotherapy in locally advanced cervical cancer. Diagnostics, 13(19), 3139.
2022
Interlenghi, M., Salvatore, C., Magni, V., Caldara, G., Schiavon, E., Cozzi, A., Schiaffino, S., Carbonaro, L., Castiglioni, I., & Sardanelli, F. (2022). A machine learning ensemble based on radiomics to predict BI-RADS category and reduce the biopsy rate of ultrasound-detected suspicious breast masses. Diagnostics, 12(1), 187.
Secchi, F., Interlenghi, M., Alì, M., Schiavon, E., Monti, C., Capra, D., Salvatore, C., Castiglioni, I., Papa, S., Sardanelli, F., & others (2022). A combined deep learning system for automatic detection of “bovine” aortic arch on computed tomography scans. Applied Sciences, 12(4), 2056.
Magni, V., Interlenghi, M., Cozzi, A., Alì, M., Salvatore, C., Azzena, A., Capra, D., Carriero, S., Della Pepa, G., Fazzini, D., & others (2022). Development and validation of an AI-driven mammographic breast density classification tool based on radiologist consensus. Radiology: Artificial Intelligence, 4(2), e210199.
Zanetti, I., Interlenghi, M., Salvatore, C., Castiglioni, I., Papa, S., & Beltramo, G. (2022). A radiomic machine learning model to predict prostate cancer response to CyberKnife treatment.. Journal of Radiosurgery & SBRT, 8.
Chiappa, V., Interlenghi, M., Salvatore, C., Fruscio, R., Ferrero, S., Rosati, F., Meis, L., Rolla, M., Maggiore, U., Ficarelli, S., & others (2022). 2022-RA-610-ESGO Radiomics and transvaginal ultrasound in adnexal masses: is the next future of diagnostics here?. International Journal of Gynecological Cancer, 32(Suppl 2), A70–A70.
Castiglioni, I., Interlenghi, M., Polidori, A., & Salvatore, C.. (2022). Method for generating models to automatically classify medical or veterinary images derived from original images into at least one class of interest.
Bogani, G., Chiappa, V., Lopez, S., Salvatore, C., Interlenghi, M., D’Oria, O., Giannini, A., Leone Roberti Maggiore, U., Chiarello, G., Palladino, S., & others (2022). Radiomics and molecular classification in endometrial cancer (the ROME study): a step forward to a simplified precision medicine. In Healthcare (pp. 2464).