Qual Quant (2017) 51:1277–1278 DOI 10.1007/s11135-016-0359-5 ERRATUM Erratum to: Artiﬁcial neural networks and their potentialities in analyzing budget health data: an application for Italy of what-if theory 1,2 1 • • Paolo Massimo Buscema Guido Maurelli 3 3 3,4 • • • Francesco Saverio Mennini Lara Gitto Simone Russo 5 5 5 • • Matteo Ruggeri Silvia Coretti Americo Cicchetti Published online: 28 June 2016 Springer Science+Business Media Dordrecht 2016 Erratum to: Qual Quant DOI 10.1007/s11135-016-0329-y In the original publication of the article, the Italian quotes starts from ‘‘La tecnica’’ and ends with ‘‘della conoscenza’’ under the heading ‘‘Methods’’ which has been included by mistake should be removed and replaced with the following English translation ‘‘The auto-encoder The online version of the original article can be found under doi:10.1007/s11135-016-0329-y. & Paolo Massimo Buscema firstname.lastname@example.org Guido Maurelli email@example.com Francesco Saverio Mennini firstname.lastname@example.org Lara Gitto email@example.com Simone Russo firstname.lastname@example.org Matteo Ruggeri email@example.com Silvia Coretti firstname.lastname@example.org Americo Cicchetti email@example.com SEMEION Research Centre of Sciences of Communication, Rome, Italy Department of Mathematical and Statistical Sciences, University of Colorado, Denver, CO, USA CEIS - Economic Evaluation and HTA (EEHTA), Faculty of Economics, University of Rome Tor Vergata, Rome, Italy Department of Statistics, University of
Quality & Quantity – Springer Journals
Published: Jun 28, 2016
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera