DE PAOLI, FEDERICA

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DE PAOLI, FEDERICA

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DIPARTIMENTO DI INGEGNERIA INDUSTRIALE E DELL'INFORMAZIONE

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Risultati 1 - 9 di 9 (tempo di esecuzione: 0.013 secondi).

A machine learning approach for the detection of incidental findings in genetic testing

2023-01-01 Berardelli, S.; De Paoli, F.; Nicora, G.; Limongelli, I.; Rizzo, E.; Magni, P.; Zucca, S.

A machine learning approach for the detection of incidental findings in genetic testing

2023-01-01 Berardelli, S.; De Paoli, F.; Nicora, G.; Limongelli, I.; Rizzo, E.; Magni, P.; Zucca, S.

An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases

2024-01-01 Zucca, S; Nicora, G; De Paoli, F; Carta, M G; Bellazzi, R; Magni, P; Rizzo, E; Limongelli, I

An automatic implementation of ACMG/ClinGen guidelines for constitutional Copy Number Variants annotation and interpretation

2020-01-01 De Paoli, F.; Limongelli, I.; Rizzo, E.; Nicora, G.; Magni, P.

Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project

2024-01-01 Stenton, S. L.; O'Leary, M. C.; Lemire, G.; Vannoy, G. E.; Ditroia, S.; Ganesh, V. S.; Groopman, E.; O'Heir, E.; Mangilog, B.; Osei-Owusu, I.; Pais, L. S.; Serrano, J.; Singer-Berk, M.; Weisburd, B.; Wilson, M. W.; Austin-Tse, C.; Abdelhakim, M.; Althagafi, A.; Babbi, G.; Bellazzi, R.; Bovo, S.; Carta, M. G.; Casadio, R.; Coenen, P. -J.; De Paoli, F.; Floris, M.; Gajapathy, M.; Hoehndorf, R.; Jacobsen, J. O. B.; Joseph, T.; Kamandula, A.; Katsonis, P.; Kint, C.; Lichtarge, O.; Limongelli, I.; Lu, Y.; Magni, P.; Mamidi, T. K. K.; Martelli, P. L.; Mulargia, M.; Nicora, G.; Nykamp, K.; Pejaver, V.; Peng, Y.; Pham, T. H. C.; Podda, M. S.; Rao, A.; Rizzo, E.; Saipradeep, V. G.; Savojardo, C.; Schols, P.; Shen, Y.; Sivadasan, N.; Smedley, D.; Soru, D.; Srinivasan, R.; Sun, Y.; Sunderam, U.; Tan, W.; Tiwari, N.; Wang, X.; Wang, Y.; Williams, A.; Worthey, E. A.; Yin, R.; You, Y.; Zeiberg, D.; Zucca, S.; Bakolitsa, C.; Brenner, S. E.; Fullerton, S. M.; Radivojac, P.; Rehm, H. L.; O'Donnell-Luria, A.

DIVAs, a phenotype-driven machine-learning model to assess the pathogenicity

2021-01-01 De Paoli, F.; Limongelli, I.; Zucca, S.; Baccalini, F.; Serpieri, V.; D'Abrusco, F.; Valente, E. M.; Magni, P.

DIVAs: a phenotype-based machine-learning model to assess the pathogenicity of digenic variant combinations

2021-01-01 De Paoli, F.; Limongelli, I.; Zucca, S.; Baccalini, F.; Serpieri, V.; D'Abrusco, F.; Zarantonello, M.; Antonaci, Fabio; Carrabba, M.; Valente, E. M.; Magni, P.

eVai's Suggested Diagnosis feature: a new AI-based method to increase diagnostic yield in Rare Disease Patients

2022-01-01 Nicora, G.; De Paoli, F.; Limongelli, I.; Rizzo, E.; Bellazzi, R.; Magni, P.; Zucca, Susanna

Phenotypic Variation in Two Siblings Affected with Shwachman-Diamond Syndrome: The Use of Expert Variant Interpreter (eVai) Suggests Clinical Relevance of a Variant in the KMT2A Gene

2022-01-01 Taha, I.; De Paoli, F.; Foroni, S.; Zucca, S.; Limongelli, I.; Cipolli, M.; Danesino, C.; Ramenghi, U.; Minelli, A.

Titolo	Data di pubblicazione	Autore(i)
A machine learning approach for the detection of incidental findings in genetic testing	1-gen-2023	Berardelli, S.; De Paoli, F.; Nicora, G.; Limongelli, I.; Rizzo, E.; Magni, P.; Zucca, S.
A machine learning approach for the detection of incidental findings in genetic testing	1-gen-2023	Berardelli, S.; De Paoli, F.; Nicora, G.; Limongelli, I.; Rizzo, E.; Magni, P.; Zucca, S.
An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases	1-gen-2024	Zucca, S; Nicora, G; De Paoli, F; Carta, M G; Bellazzi, R; Magni, P; Rizzo, E; Limongelli, I
An automatic implementation of ACMG/ClinGen guidelines for constitutional Copy Number Variants annotation and interpretation	1-gen-2020	De Paoli, F.; Limongelli, I.; Rizzo, E.; Nicora, G.; Magni, P.
Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project	1-gen-2024	Stenton, S. L.; O'Leary, M. C.; Lemire, G.; Vannoy, G. E.; Ditroia, S.; Ganesh, V. S.; Groopman, E.; O'Heir, E.; Mangilog, B.; Osei-Owusu, I.; Pais, L. S.; Serrano, J.; Singer-Berk, M.; Weisburd, B.; Wilson, M. W.; Austin-Tse, C.; Abdelhakim, M.; Althagafi, A.; Babbi, G.; Bellazzi, R.; Bovo, S.; Carta, M. G.; Casadio, R.; Coenen, P. -J.; De Paoli, F.; Floris, M.; Gajapathy, M.; Hoehndorf, R.; Jacobsen, J. O. B.; Joseph, T.; Kamandula, A.; Katsonis, P.; Kint, C.; Lichtarge, O.; Limongelli, I.; Lu, Y.; Magni, P.; Mamidi, T. K. K.; Martelli, P. L.; Mulargia, M.; Nicora, G.; Nykamp, K.; Pejaver, V.; Peng, Y.; Pham, T. H. C.; Podda, M. S.; Rao, A.; Rizzo, E.; Saipradeep, V. G.; Savojardo, C.; Schols, P.; Shen, Y.; Sivadasan, N.; Smedley, D.; Soru, D.; Srinivasan, R.; Sun, Y.; Sunderam, U.; Tan, W.; Tiwari, N.; Wang, X.; Wang, Y.; Williams, A.; Worthey, E. A.; Yin, R.; You, Y.; Zeiberg, D.; Zucca, S.; Bakolitsa, C.; Brenner, S. E.; Fullerton, S. M.; Radivojac, P.; Rehm, H. L.; O'Donnell-Luria, A.
DIVAs, a phenotype-driven machine-learning model to assess the pathogenicity	1-gen-2021	De Paoli, F.; Limongelli, I.; Zucca, S.; Baccalini, F.; Serpieri, V.; D'Abrusco, F.; Valente, E. M.; Magni, P.
DIVAs: a phenotype-based machine-learning model to assess the pathogenicity of digenic variant combinations	1-gen-2021	De Paoli, F.; Limongelli, I.; Zucca, S.; Baccalini, F.; Serpieri, V.; D'Abrusco, F.; Zarantonello, M.; Antonaci, Fabio; Carrabba, M.; Valente, E. M.; Magni, P.
eVai's Suggested Diagnosis feature: a new AI-based method to increase diagnostic yield in Rare Disease Patients	1-gen-2022	Nicora, G.; De Paoli, F.; Limongelli, I.; Rizzo, E.; Bellazzi, R.; Magni, P.; Zucca, Susanna
Phenotypic Variation in Two Siblings Affected with Shwachman-Diamond Syndrome: The Use of Expert Variant Interpreter (eVai) Suggests Clinical Relevance of a Variant in the KMT2A Gene	1-gen-2022	Taha, I.; De Paoli, F.; Foroni, S.; Zucca, S.; Limongelli, I.; Cipolli, M.; Danesino, C.; Ramenghi, U.; Minelli, A.