DE PAOLI, FEDERICA
DE PAOLI, FEDERICA
DIPARTIMENTO DI INGEGNERIA INDUSTRIALE E DELL'INFORMAZIONE
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 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.
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) | File |
|---|---|---|---|
| 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 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. | |
| 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. |