Sfoglia per Titolo
M tuberculosis in the Adjuvant Modulates Time of Appearance of CNS-Specific Effector T Cells in the Spleen through a Polymorphic Site of TLR2
2013-01-01 Nicolò, Chiara; Di Sante, Gabriele; Procoli, Annabella; Migliara, Giuseppe; Piermattei, Alessia; Valentini, Mariagrazia; Delogu, Giovanni; Cittadini, Achille; Constantin, Gabriela; Ria, Francesco
M2 Muscarinic Receptor Activation Impairs Mitotic Progression and Bipolar Mitotic Spindle Formation in Human Glioblastoma Cell Lines
2021-01-01 Di Bari, M; Tombolillo, V; Alessandrini, F; Guerriero, C; Fiore, M; Asteriti, Ia; Castigli, E; Sciaccaluga, M; Guarguaglini, G; Degrassi, F; Tata, Am.
M2 receptor activation inhibits cell cycle progression and survival in human glioblastoma cells
2013-01-01 Ferretti, M; Fabbiano, C; Di Bari, M; Conte, C; Castigli, E; Sciaccaluga, Miriam; Ponti, D; Ruggieri, P; Raco, A; Ricordy, R; Calogero, A; Tata, A. M.
M2FRED: Mobile Masked Face REcognition through periocular Dynamics analysis
2022-01-01 Cimmino, L.; Nappi, M.; Narducci, F.; Pero, C.
The m6A-independent role of epitranscriptomic factors in cancer
2024-01-01 Bove, Guglielmo; Crepaldi, Marco; Amin, Sajid; Leonard Megchelenbrink, Wouter; Nebbioso, Angela; Carafa, Vincenzo; Altucci, Lucia; Del Gaudio, Nunzio
Machine learning and COVID-19: a tool for healthcare setting choice by primary care physicians
2021-01-01 Vetrugno, G; Foti, F; Di Pumpo, M; Cicconi, M; D'Ambrosio, F; La Milia, Di; Pastorino, R; Boccia, S; Damiani, G; Laurenti, P
Machine learning and points of interest: typical tourist Italian cities
2020-01-01 Giglio, S.; Bertacchini, F.; Bilotta, E.; Pantano, P.
A Machine Learning approach for routing in satellite Mega-Constellations
2020-01-01 Cigliano, A.; Zampognaro, F.
Machine Learning Approaches for the Prediction of Postoperative Major Complications in Patients Undergoing Surgery for Bowel Obstruction
2024-01-01 Mazzotta, Alessandro D.; Burti, Elisa; Causio, Francesco Andrea; Orlandi, Alex; Martinelli, Silvia; Longaroni, Mattia; Pinciroli, Tiziana; Debs, Tarek; Costa, Gianluca; Miccini, Michelangelo; Aurello, Paolo; Petrucciani, Niccolò
Machine Learning Data Analysis Highlights the Role of Parasutterella and Alloprevotella in Autism Spectrum Disorders
2022-01-01 Pietrucci, Daniele; Teofani, Adelaide; Milanesi, Marco; Fosso, Bruno; Putignani, Lorenza; Messina, Francesco; Pesole, Graziano; Desideri, Alessandro; Chillemi, Giovanni
Machine Learning Driven Profiling of Cerebrospinal Fluid Core Biomarkers in Alzheimer's Disease and Other Neurological Disorders
2021-01-01 Bellomo, G; Indaco, A; Chiasserini, D; Maderna, E; Paolini Paoletti, F; Gaetani, L; Paciotti, S; Petricciuolo, M; Tagliavini, F; Giaccone, G; Parnetti, L; Di Fede, G
Machine learning due diligence evaluation to increase NPLs profitability transactions on secondary market
2023-01-01 Carannante, Maria; D’Amato, Valeria; Fersini, Paola; Forte, Salvatore; Melisi, Giuseppe
Machine Learning for Predicting the Low Risk of Postoperative Pancreatic Fistula After Pancreaticoduodenectomy: Toward a Dynamic and Personalized Postoperative Management Strategy
2025-01-01 Cammarata, Roberto; Ruffini, Filippo; Catamerò, Alberto; Melone, Gennaro; Costa, Gianluca; Angeletti, Silvia; Seghetti, Federico; La Vaccara, Vincenzo; Coppola, Roberto; Soda, Paolo; Guarrasi, Valerio; Caputo, Damiano
Machine Learning for Real-Time Analysis of Social Data for Disaster Management
2019-01-01 Vernier, M; Cascio, M; Foresti, G L; Farinosi, M
Machine learning for video event recognition
2021-01-01 Avola, D.; Cascio, M.; Cinque, L.; Foresti, G. L.; Pannone, D.
Machine learning in clinical and epidemiological research: Isn't it time for biostatisticians to work on it?
2019-01-01 Azzolina, D.; Baldi, I.; Barbati, G.; Berchialla, P.; Bottigliengo, D.; Bucci, A.; Calza, S.; Dolce, P.; Edefonti, V.; Faragalli, A.; Fiorito, G.; Gandin, I.; Giudici, F.; Gregori, D.; Gregorio, C.; Ieva, F.; Lanera, C.; Lorenzoni, G.; Marchioni, M.; Milanese, A.; Ricotti, A.; Sciannameo, V.; Solinas, G.; Vezzoli, M.
Machine Learning to Recognise ACL Tears: A Systematic Review
2025-01-01 Wolfgart, J. M.; Hofmann, U. K.; Praster, M.; Danalache, M.; Migliorini, F.; Feierabend, M.
Machine learning-assisted FTIR analysis of circulating extracellular vesicles for cancer liquid biopsy
2022-01-01 Di Santo, Riccardo; Vaccaro, Maria; Romanò, Sabrina; Di Giacinto, Flavio; Papi, Massimiliano; Rapaccini, Gian Ludovico; De Spirito, Marco; Miele, Luca; Basile, Umberto; Ciasca, Gabriele
Machine learning-based climate risk sharing for an insured loan in the tourism industry
2024-01-01 Carannante, Maria; D'Amato, Valeria; Fersini, Paola; Forte, Salvatore
Machine-learning assisted confocal imaging of intracellular sites of triglycerides and cholesteryl esters formation and storage
2020-01-01 Bianchetti, G; Di Giacinto, F; De Spirito, M; Maulucci, G
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| M tuberculosis in the Adjuvant Modulates Time of Appearance of CNS-Specific Effector T Cells in the Spleen through a Polymorphic Site of TLR2 | 1-gen-2013 | Nicolò, Chiara; Di Sante, Gabriele; Procoli, Annabella; Migliara, Giuseppe; Piermattei, Alessia; Valentini, Mariagrazia; Delogu, Giovanni; Cittadini, Achille; Constantin, Gabriela; Ria, Francesco | |
| M2 Muscarinic Receptor Activation Impairs Mitotic Progression and Bipolar Mitotic Spindle Formation in Human Glioblastoma Cell Lines | 1-gen-2021 | Di Bari, M; Tombolillo, V; Alessandrini, F; Guerriero, C; Fiore, M; Asteriti, Ia; Castigli, E; Sciaccaluga, M; Guarguaglini, G; Degrassi, F; Tata, Am. | |
| M2 receptor activation inhibits cell cycle progression and survival in human glioblastoma cells | 1-gen-2013 | Ferretti, M; Fabbiano, C; Di Bari, M; Conte, C; Castigli, E; Sciaccaluga, Miriam; Ponti, D; Ruggieri, P; Raco, A; Ricordy, R; Calogero, A; Tata, A. M. | |
| M2FRED: Mobile Masked Face REcognition through periocular Dynamics analysis | 1-gen-2022 | Cimmino, L.; Nappi, M.; Narducci, F.; Pero, C. | |
| The m6A-independent role of epitranscriptomic factors in cancer | 1-gen-2024 | Bove, Guglielmo; Crepaldi, Marco; Amin, Sajid; Leonard Megchelenbrink, Wouter; Nebbioso, Angela; Carafa, Vincenzo; Altucci, Lucia; Del Gaudio, Nunzio | |
| Machine learning and COVID-19: a tool for healthcare setting choice by primary care physicians | 1-gen-2021 | Vetrugno, G; Foti, F; Di Pumpo, M; Cicconi, M; D'Ambrosio, F; La Milia, Di; Pastorino, R; Boccia, S; Damiani, G; Laurenti, P | |
| Machine learning and points of interest: typical tourist Italian cities | 1-gen-2020 | Giglio, S.; Bertacchini, F.; Bilotta, E.; Pantano, P. | |
| A Machine Learning approach for routing in satellite Mega-Constellations | 1-gen-2020 | Cigliano, A.; Zampognaro, F. | |
| Machine Learning Approaches for the Prediction of Postoperative Major Complications in Patients Undergoing Surgery for Bowel Obstruction | 1-gen-2024 | Mazzotta, Alessandro D.; Burti, Elisa; Causio, Francesco Andrea; Orlandi, Alex; Martinelli, Silvia; Longaroni, Mattia; Pinciroli, Tiziana; Debs, Tarek; Costa, Gianluca; Miccini, Michelangelo; Aurello, Paolo; Petrucciani, Niccolò | |
| Machine Learning Data Analysis Highlights the Role of Parasutterella and Alloprevotella in Autism Spectrum Disorders | 1-gen-2022 | Pietrucci, Daniele; Teofani, Adelaide; Milanesi, Marco; Fosso, Bruno; Putignani, Lorenza; Messina, Francesco; Pesole, Graziano; Desideri, Alessandro; Chillemi, Giovanni | |
| Machine Learning Driven Profiling of Cerebrospinal Fluid Core Biomarkers in Alzheimer's Disease and Other Neurological Disorders | 1-gen-2021 | Bellomo, G; Indaco, A; Chiasserini, D; Maderna, E; Paolini Paoletti, F; Gaetani, L; Paciotti, S; Petricciuolo, M; Tagliavini, F; Giaccone, G; Parnetti, L; Di Fede, G | |
| Machine learning due diligence evaluation to increase NPLs profitability transactions on secondary market | 1-gen-2023 | Carannante, Maria; D’Amato, Valeria; Fersini, Paola; Forte, Salvatore; Melisi, Giuseppe | |
| Machine Learning for Predicting the Low Risk of Postoperative Pancreatic Fistula After Pancreaticoduodenectomy: Toward a Dynamic and Personalized Postoperative Management Strategy | 1-gen-2025 | Cammarata, Roberto; Ruffini, Filippo; Catamerò, Alberto; Melone, Gennaro; Costa, Gianluca; Angeletti, Silvia; Seghetti, Federico; La Vaccara, Vincenzo; Coppola, Roberto; Soda, Paolo; Guarrasi, Valerio; Caputo, Damiano | |
| Machine Learning for Real-Time Analysis of Social Data for Disaster Management | 1-gen-2019 | Vernier, M; Cascio, M; Foresti, G L; Farinosi, M | |
| Machine learning for video event recognition | 1-gen-2021 | Avola, D.; Cascio, M.; Cinque, L.; Foresti, G. L.; Pannone, D. | |
| Machine learning in clinical and epidemiological research: Isn't it time for biostatisticians to work on it? | 1-gen-2019 | Azzolina, D.; Baldi, I.; Barbati, G.; Berchialla, P.; Bottigliengo, D.; Bucci, A.; Calza, S.; Dolce, P.; Edefonti, V.; Faragalli, A.; Fiorito, G.; Gandin, I.; Giudici, F.; Gregori, D.; Gregorio, C.; Ieva, F.; Lanera, C.; Lorenzoni, G.; Marchioni, M.; Milanese, A.; Ricotti, A.; Sciannameo, V.; Solinas, G.; Vezzoli, M. | |
| Machine Learning to Recognise ACL Tears: A Systematic Review | 1-gen-2025 | Wolfgart, J. M.; Hofmann, U. K.; Praster, M.; Danalache, M.; Migliorini, F.; Feierabend, M. | |
| Machine learning-assisted FTIR analysis of circulating extracellular vesicles for cancer liquid biopsy | 1-gen-2022 | Di Santo, Riccardo; Vaccaro, Maria; Romanò, Sabrina; Di Giacinto, Flavio; Papi, Massimiliano; Rapaccini, Gian Ludovico; De Spirito, Marco; Miele, Luca; Basile, Umberto; Ciasca, Gabriele | |
| Machine learning-based climate risk sharing for an insured loan in the tourism industry | 1-gen-2024 | Carannante, Maria; D'Amato, Valeria; Fersini, Paola; Forte, Salvatore | |
| Machine-learning assisted confocal imaging of intracellular sites of triglycerides and cholesteryl esters formation and storage | 1-gen-2020 | Bianchetti, G; Di Giacinto, F; De Spirito, M; Maulucci, G |
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