Silva, Matteo
Silva, Matteo
MILANO - Dipartimento di Filosofia
High-resolution CT phenotypes in pulmonary sarcoidosis: a multinational Delphi consensus study
2024 Desai, S. R.; Sivarasan, N.; Johannson, K. A.; George, P. M.; Culver, D. A.; Devaraj, A.; Lynch, D. A.; Milne, D.; Renzoni, E.; Nunes, H.; Sverzellati, N.; Spagnolo, P.; Baughman, R. P.; Yadav, R.; Piciucchi, S.; Walsh, S. L. F.; Kouranos, V.; Wells, A. U.; Anderson, A.; Morgenthau, A.; Gaser, A.; Vizel, A.; Speranskaya, A.; Gerke, A.; Goksel, A.; Undurraga, A.; Sharma, A.; Oh, A.; Leung, A.; Larici, Anna Rita; Prasse, A.; Mazzei, A.; Morais, A.; Bhalla, A.; Del Rio, B.; Jankharia, B.; Elicker, B.; Pereira, C.; Biegelman-Aubry, C.; White, C.; Ravaglia, C.; Hsia, C.; Schaefer-Prokop, C.; Launay, D.; Talwar, D.; Castillo, D.; Patel, D.; Israel-Biet, D.; Valeyre, D.; Britt, E. J.; Bargagli, E.; Bendstrup, E.; Crouser, E.; Nossent, E.; Shmelev, E.; Porquera, E. C.; Bonella, F.; Cohen-Aubart, F.; Jeny, F.; Ferrara, G.; Jin, G. Y.; Robbie, H.; Prosch, H.; Sumikawa, H.; Ling-Pei, H.; Lee, H. Y.; Strambu, I.; Buendia-Roldan, I.; Grutters, J.; Ryu, J.; Swigris, J.; Miedema, J.; Goo, J. M.; Barnett, J.; Verschakelen, J.; Goldin, J.; Seo, J. B.; Enghelmayer, J.; Mana, J.; Behr, J.; Patterson, K.; Antoniou, K.; Brown, K.; Fujimoto, K.; Savale, L.; Maier, L.; Richeldi, Luca; Neto, M. L. R.; Humbert, M.; Judson, M.; Veltkamp, M.; Wilsher, M.; Molina, M.; Otaola, M.; Revel, M. -P.; Silva, Matteo; Drent, M.; Schiebler, M.; Wijsenbeek-Lourens, M.; Bonifazi, M.; Remy-Jardin, M.; Koslow, M.; Balter, M.; Kreuter, M.; Thillai, M.; Hamzeh, N.; Chaudhuri, N.; Mogulkoc, N.; Todd, N.; Screaton, N.; Goh, N.; Shah, N.; Obi, O.; Shlobin, O.; Baranova, O.; Bresser, P.; Rottoli, P.; Brillet, P. -Y.; Said-Hartley, Q.; Borie, R.; Mostard, R.; van Zyl-smit, R.; Kairalla, R.; Egashira, R.; Boussouar, S.; Lee, S. M.; Bhalla, S.; Tomassetti, S.; Quadrelli, S.; Hart, S. P.; Danoff, S.; Rajan, S.; Choi, S. M.; Copley, S.; Kim, T. J.; Johkoh, T.; Corte, T.; Mcloud, T.; Wessendorf, T.; Alfaro, T.; Arai, T.; Costabel, U.; Vicens-Zygmunt, V.; Poletti, Valentina; Cottin, V.; Vucinic, V.; Wuyts, W.; van Es, W.; Jeong, Y. J.; Inoue, Y.
A deep learning algorithm for predicting disease progression in idiopathic pulmonary fibrosis
2023 Fang, Yy; Felder, F; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Cooper, W; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S
A deep learning algorithm for predicting disease progression in idiopathic pulmonary fibrosis
2023 Fang, Yy; Felder, F; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Cooper, W; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S
Curriculum for bariatric endoscopy and endoscopic treatment of the complications of bariatric surgery: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement
2023 Boskoski, Ivo; Pontecorvi, Valerio; Ibrahim, M.; Huberty, V.; Maselli, R.; Gölder, S. K.; Kral, J.; Samanta, J.; Patai, Á. V.; Haidry, R.; Hollenbach, M.; Pérez-Cuadrado-Robles, E.; Silva, Matteo; Messmann, H.; Tham, T. C.; Bisschops, R.
Deep learning-based quantification of traction bronchiectasis severity for predicting outcome in idiopathic pulmonary fibrosis
2023 Felder, F; Nan, Y; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Glaspole, I; Goh, N; Cooper, W; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S
Deep learning-based quantification of traction bronchiectasis severity for predicting outcome in idiopathic pulmonary fibrosis
2023 Felder, F; Nan, Y; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Glaspole, I; Goh, N; Cooper, W; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S
Late Breaking Abstract - Deep learning-based outcome prediction in pulmonary fibrosos using synthetic HRCT
2023 Walsh, S; Xing, Xd; Mackintosh, J; Calandriello, Lucio; Fang, Yy; Wang, Sy; Zhang, Shuya; Nan, Y; Silva, Matteo; Wells, A; Yang, G; Corte, T
Late Breaking Abstract - Deep learning-based outcome prediction in pulmonary fibrosos using synthetic HRCT
2023 Walsh, S; Xing, Xd; Mackintosh, J; Calandriello, Lucio; Fang, Yy; Wang, Sy; Zhang, Shuya; Nan, Y; Silva, Matteo; Wells, A; Yang, G; Corte, T
Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography
2022 Walsh, S. L. F.; Mackintosh, J. A.; Calandriello, Lucio; Silva, Matteo; Sverzellati, N.; Larici, Anna Rita; Humphries, S. M.; Lynch, D. A.; Jo, H. E.; Glaspole, I.; Grainge, C.; Goh, N.; Hopkins, P. M. A.; Moodley, Y.; Reynolds, P. N.; Zappala, C.; Keir, G.; Cooper, W. A.; Mahar, A. M.; Ellis, S.; Wells, A. U.; Corte, T. J.
SIMILARITY INDEX TO DEFINITE USUAL INTERSTITIAL PNEUMONIA (SI-UIP): A NOVEL PROGNOSTIC TOOL PROPOSED BY THE AUSTRALIAN IDIOPATHIC PULMONARY FIBROSIS REGISTRY
2021 Mackintosh, J; Silva, Matteo; Calandriello, Lucio; Humphries, S; Lynch, D; Jo, H; Glaspole, I; Grainge, C; Goh, N; Hopkins, P; Moodley, Y; Reynolds, P; Zappala, C; Allan, H; Keir, G; Hayen, A; Cooper, W; Mahar, A; Ellis, S; Macansh, S; Wells, A; Walsh, S; Corte, T
Deep Learning-Based Prediction of Progressive Fibrotic Lung Disease on Baseline Computed Tomography in the Australian IPF Registry
2020 Jo, H; Corte, Tj; Calandriello, Lucio; Silva, Matteo; Sverzellati, N; Chapman, S; Cooper, W; Ellis, S; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Keir, Gj; Maher, A; Moodley, Yi; Reynolds, Pn; Walters, Eh; Leigh, L; Oldmeadow, C; Humphries, Sm; Lynch, Da; Walsh, Sl
Validation of Deep Learning-Based Diagnostic Likelihoods of Usual Interstitial Pneumonia on Baseline Computed Tomography in the Australian IPF Registry
2020 Jo, H; Corte, Tj; Calandriello, Lucio; Silva, Matteo; Sverzellati, N; Humphries, Sm; Lynch, Da; Chapman, S; Cooper, W; Ellis, S; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Keir, Gj; Maher, A; Moodley, Yi; Reynolds, Pn; Walters, Eh; Zappala, Cj; Leigh, L; Oldmeadow, C; Heinze, S; Mccormack, S; Miller, A; Ng, B; Rouse, H; Walsh, Sl
A Deep Learning Algorithm for Classifying Fibrotic Lung Disease on High Resolution Computed Tomography
2018 Walsh, Slf; Calandriello, Lucio; Silva, Matteo; Sverzellati, N
Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study
2018 Walsh, Slf; Calandriello, Lucio; Silva, Matteo; Sverzellati, N
Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study
2018 Walsh, Slf; Calandriello, Lucio; Silva, Matteo; Sverzellati, N
Late Breaking Abstract - A Deep Learning Algorithm for Classifying Fibrotic Lung Disease on High Resolution Computed Tomography
2018 Walsh, S; Calandriello, Lucio; Silva, Matteo; Sverzellati, N
| Data di pubblicazione | Titolo | Autore(i) | File |
|---|---|---|---|
| 1-gen-2024 | High-resolution CT phenotypes in pulmonary sarcoidosis: a multinational Delphi consensus study | Desai, S. R.; Sivarasan, N.; Johannson, K. A.; George, P. M.; Culver, D. A.; Devaraj, A.; Lynch, D. A.; Milne, D.; Renzoni, E.; Nunes, H.; Sverzellati, N.; Spagnolo, P.; Baughman, R. P.; Yadav, R.; Piciucchi, S.; Walsh, S. L. F.; Kouranos, V.; Wells, A. U.; Anderson, A.; Morgenthau, A.; Gaser, A.; Vizel, A.; Speranskaya, A.; Gerke, A.; Goksel, A.; Undurraga, A.; Sharma, A.; Oh, A.; Leung, A.; Larici, Anna Rita; Prasse, A.; Mazzei, A.; Morais, A.; Bhalla, A.; Del Rio, B.; Jankharia, B.; Elicker, B.; Pereira, C.; Biegelman-Aubry, C.; White, C.; Ravaglia, C.; Hsia, C.; Schaefer-Prokop, C.; Launay, D.; Talwar, D.; Castillo, D.; Patel, D.; Israel-Biet, D.; Valeyre, D.; Britt, E. J.; Bargagli, E.; Bendstrup, E.; Crouser, E.; Nossent, E.; Shmelev, E.; Porquera, E. C.; Bonella, F.; Cohen-Aubart, F.; Jeny, F.; Ferrara, G.; Jin, G. Y.; Robbie, H.; Prosch, H.; Sumikawa, H.; Ling-Pei, H.; Lee, H. Y.; Strambu, I.; Buendia-Roldan, I.; Grutters, J.; Ryu, J.; Swigris, J.; Miedema, J.; Goo, J. M.; Barnett, J.; Verschakelen, J.; Goldin, J.; Seo, J. B.; Enghelmayer, J.; Mana, J.; Behr, J.; Patterson, K.; Antoniou, K.; Brown, K.; Fujimoto, K.; Savale, L.; Maier, L.; Richeldi, Luca; Neto, M. L. R.; Humbert, M.; Judson, M.; Veltkamp, M.; Wilsher, M.; Molina, M.; Otaola, M.; Revel, M. -P.; Silva, Matteo; Drent, M.; Schiebler, M.; Wijsenbeek-Lourens, M.; Bonifazi, M.; Remy-Jardin, M.; Koslow, M.; Balter, M.; Kreuter, M.; Thillai, M.; Hamzeh, N.; Chaudhuri, N.; Mogulkoc, N.; Todd, N.; Screaton, N.; Goh, N.; Shah, N.; Obi, O.; Shlobin, O.; Baranova, O.; Bresser, P.; Rottoli, P.; Brillet, P. -Y.; Said-Hartley, Q.; Borie, R.; Mostard, R.; van Zyl-smit, R.; Kairalla, R.; Egashira, R.; Boussouar, S.; Lee, S. M.; Bhalla, S.; Tomassetti, S.; Quadrelli, S.; Hart, S. P.; Danoff, S.; Rajan, S.; Choi, S. M.; Copley, S.; Kim, T. J.; Johkoh, T.; Corte, T.; Mcloud, T.; Wessendorf, T.; Alfaro, T.; Arai, T.; Costabel, U.; Vicens-Zygmunt, V.; Poletti, Valentina; Cottin, V.; Vucinic, V.; Wuyts, W.; van Es, W.; Jeong, Y. J.; Inoue, Y. | |
| 1-gen-2023 | A deep learning algorithm for predicting disease progression in idiopathic pulmonary fibrosis | Fang, Yy; Felder, F; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Cooper, W; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S | |
| 1-gen-2023 | A deep learning algorithm for predicting disease progression in idiopathic pulmonary fibrosis | Fang, Yy; Felder, F; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Cooper, W; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S | |
| 1-gen-2023 | Curriculum for bariatric endoscopy and endoscopic treatment of the complications of bariatric surgery: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement | Boskoski, Ivo; Pontecorvi, Valerio; Ibrahim, M.; Huberty, V.; Maselli, R.; Gölder, S. K.; Kral, J.; Samanta, J.; Patai, Á. V.; Haidry, R.; Hollenbach, M.; Pérez-Cuadrado-Robles, E.; Silva, Matteo; Messmann, H.; Tham, T. C.; Bisschops, R. | |
| 1-gen-2023 | Deep learning-based quantification of traction bronchiectasis severity for predicting outcome in idiopathic pulmonary fibrosis | Felder, F; Nan, Y; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Glaspole, I; Goh, N; Cooper, W; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S | |
| 1-gen-2023 | Deep learning-based quantification of traction bronchiectasis severity for predicting outcome in idiopathic pulmonary fibrosis | Felder, F; Nan, Y; Yang, G; Mackintosh, J; Calandriello, Lucio; Silva, Matteo; Glaspole, I; Goh, N; Cooper, W; Grainge, C; Hopkins, P; Moodley, Y; Vidya, N; Reynolds, P; Wells, A; Corte, T; Walsh, S | |
| 1-gen-2023 | Late Breaking Abstract - Deep learning-based outcome prediction in pulmonary fibrosos using synthetic HRCT | Walsh, S; Xing, Xd; Mackintosh, J; Calandriello, Lucio; Fang, Yy; Wang, Sy; Zhang, Shuya; Nan, Y; Silva, Matteo; Wells, A; Yang, G; Corte, T | |
| 1-gen-2023 | Late Breaking Abstract - Deep learning-based outcome prediction in pulmonary fibrosos using synthetic HRCT | Walsh, S; Xing, Xd; Mackintosh, J; Calandriello, Lucio; Fang, Yy; Wang, Sy; Zhang, Shuya; Nan, Y; Silva, Matteo; Wells, A; Yang, G; Corte, T | |
| 1-gen-2022 | Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography | Walsh, S. L. F.; Mackintosh, J. A.; Calandriello, Lucio; Silva, Matteo; Sverzellati, N.; Larici, Anna Rita; Humphries, S. M.; Lynch, D. A.; Jo, H. E.; Glaspole, I.; Grainge, C.; Goh, N.; Hopkins, P. M. A.; Moodley, Y.; Reynolds, P. N.; Zappala, C.; Keir, G.; Cooper, W. A.; Mahar, A. M.; Ellis, S.; Wells, A. U.; Corte, T. J. | |
| 1-gen-2021 | SIMILARITY INDEX TO DEFINITE USUAL INTERSTITIAL PNEUMONIA (SI-UIP): A NOVEL PROGNOSTIC TOOL PROPOSED BY THE AUSTRALIAN IDIOPATHIC PULMONARY FIBROSIS REGISTRY | Mackintosh, J; Silva, Matteo; Calandriello, Lucio; Humphries, S; Lynch, D; Jo, H; Glaspole, I; Grainge, C; Goh, N; Hopkins, P; Moodley, Y; Reynolds, P; Zappala, C; Allan, H; Keir, G; Hayen, A; Cooper, W; Mahar, A; Ellis, S; Macansh, S; Wells, A; Walsh, S; Corte, T | |
| 1-gen-2020 | Deep Learning-Based Prediction of Progressive Fibrotic Lung Disease on Baseline Computed Tomography in the Australian IPF Registry | Jo, H; Corte, Tj; Calandriello, Lucio; Silva, Matteo; Sverzellati, N; Chapman, S; Cooper, W; Ellis, S; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Keir, Gj; Maher, A; Moodley, Yi; Reynolds, Pn; Walters, Eh; Leigh, L; Oldmeadow, C; Humphries, Sm; Lynch, Da; Walsh, Sl | |
| 1-gen-2020 | Validation of Deep Learning-Based Diagnostic Likelihoods of Usual Interstitial Pneumonia on Baseline Computed Tomography in the Australian IPF Registry | Jo, H; Corte, Tj; Calandriello, Lucio; Silva, Matteo; Sverzellati, N; Humphries, Sm; Lynch, Da; Chapman, S; Cooper, W; Ellis, S; Glaspole, I; Goh, N; Grainge, C; Hopkins, P; Keir, Gj; Maher, A; Moodley, Yi; Reynolds, Pn; Walters, Eh; Zappala, Cj; Leigh, L; Oldmeadow, C; Heinze, S; Mccormack, S; Miller, A; Ng, B; Rouse, H; Walsh, Sl | |
| 1-gen-2018 | A Deep Learning Algorithm for Classifying Fibrotic Lung Disease on High Resolution Computed Tomography | Walsh, Slf; Calandriello, Lucio; Silva, Matteo; Sverzellati, N | |
| 1-gen-2018 | Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study | Walsh, Slf; Calandriello, Lucio; Silva, Matteo; Sverzellati, N | |
| 1-gen-2018 | Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study | Walsh, Slf; Calandriello, Lucio; Silva, Matteo; Sverzellati, N | |
| 1-gen-2018 | Late Breaking Abstract - A Deep Learning Algorithm for Classifying Fibrotic Lung Disease on High Resolution Computed Tomography | Walsh, S; Calandriello, Lucio; Silva, Matteo; Sverzellati, N |