Fully Synthetic Longitudinal Real-World Data From Hearing Aid Wearers for Public Health Policy Modeling

Articolo
Data di Pubblicazione:
2019
Citazione:
Fully Synthetic Longitudinal Real-World Data From Hearing Aid Wearers for Public Health Policy Modeling / C. Jeppe H., P. Niels H., R. Rikke, M. Anisetti, B. Doris-Eva, S. George, M. Louisa, B. Thanos, K. Dimitris, D. Nikos, G. Giorgos, E. Apostolos. - In: FRONTIERS IN NEUROSCIENCE. - ISSN 1662-453X. - 13(2019 Aug 13). [10.3389/fnins.2019.00850]
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
real-world data; longitudinal data; hearing aids; public health policy; evidence-based; hearing loss; sound exposure;
Elenco autori:
C. Jeppe H., P. Niels H., R. Rikke, M. Anisetti, B. Doris-Eva, S. George, M. Louisa, B. Thanos, K. Dimitris, D. Nikos, G. Giorgos, E. Apostolos
Autori di Ateneo:
ANISETTI MARCO ( autore )
Link alla scheda completa:
https://air.unimi.it/handle/2434/713030
Link al Full Text:
Progetto:
EVidenced based management of hearing impairments: Public health p?licy making based on fusing big data analytics and simulaTION

Aree Di Ricerca

Settori


Settore INF/01 - Informatica