Sfoglia per Titolo
M1-polarized macrophages as predictor of poor response to trabectedin treatment in myxoid liposarcoma
2016-01-01 Vincenzi, Bruno; Fioramonti, Marco; Iuliani, Michele; Pantano, Francesco; Ribelli, Giulia; Santini, Daniele; Tonini, Giuseppe
Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers
2022-01-01 Farinella, F.; Merone, M.; Bacco, L.; Capirchio, A.; Ciccozzi, M.; Caligiore, D.
Machine Learning and Criminal Justice: A Systematic Review of Advanced Methodology for Recidivism Risk Prediction
2022-01-01 Travaini, G. V.; Pacchioni, F.; Bellumore, S.; Bosia, M.; De Micco, F.
A machine learning approach for sentiment analysis for Italian reviews in healthcare
2020-01-01 Bacco, L.; Cimino, A.; Paulon, L.; Merone, M.; Dell'Orletta, F.
A Machine Learning Approach for Predicting Electrophysiological Responses in Genetically Modified HEK Cells
2024-01-01 Vitale, J.; Sassi, M.; Pecchia, L.
A machine learning approach to identify clusters of patients with different Breakthrough cancer Pain (BTcP) clinical features and specific opioids response
2020-07-09 Armento, Grazia
Machine learning can predict anterior elevation after reverse total shoulder arthroplasty: A new tool for daily outpatient clinic?
2024-01-01 Franceschetti, Edoardo; Gregori, Pietro; De Giorgi, Simone; Martire, Tommaso; Za, Pierangelo; Papalia, Giuseppe Francesco; Giurazza, Giancarlo; Longo, Umile Giuseppe; Papalia, Rocco
Machine learning for exploring neurophysiological functionality in multiple sclerosis based on trigeminal and hand blink reflexes
2022-01-01 Biggio, Monica; Caligiore, Daniele; D'Antoni, Federico; Bove, Marco; Merone, Mario
Machine learning for predicting levetiracetam treatment response in temporal lobe epilepsy
2021-01-01 Croce, Pierpaolo; Ricci, Lorenzo; Pulitano, Patrizia; Boscarino, Marilisa; Zappasodi, Filippo; Lanzone, Jacopo; Narducci, Flavia; Mecarelli, Oriano; Di Lazzaro, Vincenzo; Tombini, Mario; Assenza, Giovanni
Machine Learning for Threat Recognition in Critical Cyber-Physical Systems
2021-01-01 Perrone, Paola; Flammini, Francesco; Setola, Roberto
Machine learning in primary biliary cholangitis: A novel approach for risk stratification
2022-01-01 Gerussi, A.; Verda, D.; Bernasconi, D. P.; Carbone, M.; Komori, A.; Abe, M.; Inao, M.; Namisaki, T.; Mochida, S.; Yoshiji, H.; Hirschfield, G.; Lindor, K.; Pares, A.; Corpechot, C.; Cazzagon, N.; Floreani, A.; Marzioni, M.; Alvaro, D.; Vespasiani Gentilucci, U.; Cristoferi, L.; Valsecchi, M. G.; Muselli, M.; Hansen, B. E.; Tanaka, A.; Invernizzi, P.
A machine learning model for supporting symptom-based referral and diagnosis of bronchitis and pneumonia in limited resource settings
2021-01-01 Stokes, K.; Castaldo, R.; Franzese, M.; Salvatore, M.; Fico, G.; Pokvic, L. G.; Badnjevic, A.; Pecchia, L.
Machine learning models exploring characteristic single-nucleotide signatures in yellow fever virus
2022-01-01 Salgado, Álvaro; Melo-Minardi, Raquel C. de; Giovanetti, Marta; Veloso, Adriano; Morais-Rodrigues, Francielly; Adelino, Talita; de Jesus, Ronaldo; Tosta, Stephane; Azevedo, Vasco; Lourenco, José; Alcantara, Luiz Carlos J.
A machine-learning approach to cardiovascular risk prediction in psoriatic arthritis
2020-01-01 Navarini, Luca; Sperti, Michela; Currado, Damiano; Costa, Luisa; Deriu, Marco A; Margiotta, Domenico Paolo Emanuele; Tasso, Marco; Scarpa, Raffaele; Afeltra, Antonella; Caso, Francesco
Machine-learning prediction of treatment response to stereotactic body radiation therapy in oligometastatic gynecological cancer: A multi-institutional study
2024-01-01 Cilla, S.; Campitelli, M.; Antonietta Gambacorta, M.; Michela Rinaldi, R.; Deodato, F.; Pezzulla, D.; Romano, C.; Fodor, A.; Laliscia, C.; Trippa, F.; De Sanctis, V.; Ippolito, E.; Ferioli, M.; Titone, F.; Russo, D.; Balcet, V.; Vicenzi, L.; Di Cataldo, V.; Raguso, A.; Giuseppe Morganti, A.; Ferrandina, G.; Macchia, G.
A machine-learning-based approach to solve both contact location and force in soft material tactile sensors
2020-01-01 Massari, L; Schena, E; Massaroni, C; Saccomandi, P; Menciassi, A; Sinibaldi, E; Oddo, Cm
The machine-like repair of aging. Disentangling the key assumptions of the SENS agenda
2022-01-01 García-Barranquero, Pablo; Bertolaso, Marta
Machine/Animal Hybrid Controllers for Space Applications - Final Report
2008-01-01 A. Benvenuto, G. Di Pino; Sergi, F.; Campolo, D.; Accoto, D; Assenza, G.; Rossini, P. M.; Guglielmelli, E.
Macitentan inhibits the transforming growth factor-β profibrotic action, blocking the signaling mediated by the ETR/TβRI complex in systemic sclerosis dermal fibroblasts
2015-01-01 Cipriani, Paola; DI BENEDETTO, Paola; Ruscitti, Piero; Verzella, Daniela; Fischietti, Mariafausta; Zazzeroni, Francesca; Liakouli, Vasiliki; Carubbi, Francesco; Berardicurti, Onorina; Alesse, Edoardo; Giacomelli, Roberto
Macrolide resistance genotypes and phenotypes among erythromycin-resistant clinical isolates of Staphylococcus aureus and coagulase-negative staphylococci, Italy
2009-01-01 Gherardi, G; DE FLORIO, L; Lorino, G; Fico, L; Dicuonzo, G
Titolo | Data di pubblicazione | Autore(i) | File |
---|---|---|---|
M1-polarized macrophages as predictor of poor response to trabectedin treatment in myxoid liposarcoma | 1-gen-2016 | Vincenzi, Bruno; Fioramonti, Marco; Iuliani, Michele; Pantano, Francesco; Ribelli, Giulia; Santini, Daniele; Tonini, Giuseppe | |
Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers | 1-gen-2022 | Farinella, F.; Merone, M.; Bacco, L.; Capirchio, A.; Ciccozzi, M.; Caligiore, D. | |
Machine Learning and Criminal Justice: A Systematic Review of Advanced Methodology for Recidivism Risk Prediction | 1-gen-2022 | Travaini, G. V.; Pacchioni, F.; Bellumore, S.; Bosia, M.; De Micco, F. | |
A machine learning approach for sentiment analysis for Italian reviews in healthcare | 1-gen-2020 | Bacco, L.; Cimino, A.; Paulon, L.; Merone, M.; Dell'Orletta, F. | |
A Machine Learning Approach for Predicting Electrophysiological Responses in Genetically Modified HEK Cells | 1-gen-2024 | Vitale, J.; Sassi, M.; Pecchia, L. | |
A machine learning approach to identify clusters of patients with different Breakthrough cancer Pain (BTcP) clinical features and specific opioids response | 9-lug-2020 | Armento, Grazia | |
Machine learning can predict anterior elevation after reverse total shoulder arthroplasty: A new tool for daily outpatient clinic? | 1-gen-2024 | Franceschetti, Edoardo; Gregori, Pietro; De Giorgi, Simone; Martire, Tommaso; Za, Pierangelo; Papalia, Giuseppe Francesco; Giurazza, Giancarlo; Longo, Umile Giuseppe; Papalia, Rocco | |
Machine learning for exploring neurophysiological functionality in multiple sclerosis based on trigeminal and hand blink reflexes | 1-gen-2022 | Biggio, Monica; Caligiore, Daniele; D'Antoni, Federico; Bove, Marco; Merone, Mario | |
Machine learning for predicting levetiracetam treatment response in temporal lobe epilepsy | 1-gen-2021 | Croce, Pierpaolo; Ricci, Lorenzo; Pulitano, Patrizia; Boscarino, Marilisa; Zappasodi, Filippo; Lanzone, Jacopo; Narducci, Flavia; Mecarelli, Oriano; Di Lazzaro, Vincenzo; Tombini, Mario; Assenza, Giovanni | |
Machine Learning for Threat Recognition in Critical Cyber-Physical Systems | 1-gen-2021 | Perrone, Paola; Flammini, Francesco; Setola, Roberto | |
Machine learning in primary biliary cholangitis: A novel approach for risk stratification | 1-gen-2022 | Gerussi, A.; Verda, D.; Bernasconi, D. P.; Carbone, M.; Komori, A.; Abe, M.; Inao, M.; Namisaki, T.; Mochida, S.; Yoshiji, H.; Hirschfield, G.; Lindor, K.; Pares, A.; Corpechot, C.; Cazzagon, N.; Floreani, A.; Marzioni, M.; Alvaro, D.; Vespasiani Gentilucci, U.; Cristoferi, L.; Valsecchi, M. G.; Muselli, M.; Hansen, B. E.; Tanaka, A.; Invernizzi, P. | |
A machine learning model for supporting symptom-based referral and diagnosis of bronchitis and pneumonia in limited resource settings | 1-gen-2021 | Stokes, K.; Castaldo, R.; Franzese, M.; Salvatore, M.; Fico, G.; Pokvic, L. G.; Badnjevic, A.; Pecchia, L. | |
Machine learning models exploring characteristic single-nucleotide signatures in yellow fever virus | 1-gen-2022 | Salgado, Álvaro; Melo-Minardi, Raquel C. de; Giovanetti, Marta; Veloso, Adriano; Morais-Rodrigues, Francielly; Adelino, Talita; de Jesus, Ronaldo; Tosta, Stephane; Azevedo, Vasco; Lourenco, José; Alcantara, Luiz Carlos J. | |
A machine-learning approach to cardiovascular risk prediction in psoriatic arthritis | 1-gen-2020 | Navarini, Luca; Sperti, Michela; Currado, Damiano; Costa, Luisa; Deriu, Marco A; Margiotta, Domenico Paolo Emanuele; Tasso, Marco; Scarpa, Raffaele; Afeltra, Antonella; Caso, Francesco | |
Machine-learning prediction of treatment response to stereotactic body radiation therapy in oligometastatic gynecological cancer: A multi-institutional study | 1-gen-2024 | Cilla, S.; Campitelli, M.; Antonietta Gambacorta, M.; Michela Rinaldi, R.; Deodato, F.; Pezzulla, D.; Romano, C.; Fodor, A.; Laliscia, C.; Trippa, F.; De Sanctis, V.; Ippolito, E.; Ferioli, M.; Titone, F.; Russo, D.; Balcet, V.; Vicenzi, L.; Di Cataldo, V.; Raguso, A.; Giuseppe Morganti, A.; Ferrandina, G.; Macchia, G. | |
A machine-learning-based approach to solve both contact location and force in soft material tactile sensors | 1-gen-2020 | Massari, L; Schena, E; Massaroni, C; Saccomandi, P; Menciassi, A; Sinibaldi, E; Oddo, Cm | |
The machine-like repair of aging. Disentangling the key assumptions of the SENS agenda | 1-gen-2022 | García-Barranquero, Pablo; Bertolaso, Marta | |
Machine/Animal Hybrid Controllers for Space Applications - Final Report | 1-gen-2008 | A. Benvenuto, G. Di Pino; Sergi, F.; Campolo, D.; Accoto, D; Assenza, G.; Rossini, P. M.; Guglielmelli, E. | |
Macitentan inhibits the transforming growth factor-β profibrotic action, blocking the signaling mediated by the ETR/TβRI complex in systemic sclerosis dermal fibroblasts | 1-gen-2015 | Cipriani, Paola; DI BENEDETTO, Paola; Ruscitti, Piero; Verzella, Daniela; Fischietti, Mariafausta; Zazzeroni, Francesca; Liakouli, Vasiliki; Carubbi, Francesco; Berardicurti, Onorina; Alesse, Edoardo; Giacomelli, Roberto | |
Macrolide resistance genotypes and phenotypes among erythromycin-resistant clinical isolates of Staphylococcus aureus and coagulase-negative staphylococci, Italy | 1-gen-2009 | Gherardi, G; DE FLORIO, L; Lorino, G; Fico, L; Dicuonzo, G |
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