{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T04:10:36Z","timestamp":1748059836942,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":9,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819609932"},{"type":"electronic","value":"9789819609949"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-0994-9_29","type":"book-chapter","created":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T13:23:39Z","timestamp":1748006619000},"page":"311-322","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Corporate Financial Distress Prediction with Machine Learning Techniques"],"prefix":"10.1007","author":[{"given":"Claudio","family":"Pizzi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Federico","family":"Farsura","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Corazza","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesca","family":"Parpinel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,24]]},"reference":[{"issue":"4","key":"29_CR1","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1111\/j.1540-6261.1968.tb00843.x","volume":"23","author":"EI Altman","year":"1968","unstructured":"Altman, E.I.: Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J. Financ. 23(4), 589\u2013609 (1968)","journal-title":"J. Financ."},{"key":"29_CR2","doi-asserted-by":"crossref","unstructured":"Altman, E.I., Sabato, G.: Modeling credit risk for SMEs: evidence from the U.S. Market. Abacus 43(3), 332\u2013357 (2007)","DOI":"10.1111\/j.1467-6281.2007.00234.x"},{"key":"29_CR3","doi-asserted-by":"crossref","unstructured":"Altman, E.I., Sabato, G., Wilson, N.: The value of non-financial information in SME risk management. J. Credit Risk 6(2), 1\u201333 (2010)","DOI":"10.21314\/JCR.2010.110"},{"issue":"2","key":"29_CR4","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1016\/j.ejor.2015.07.062","volume":"249","author":"G Andreeva","year":"2016","unstructured":"Andreeva, G., Calabrese, R., Osmetti, S.: A: A comparative analysis of the UK and Italian small businesses using generalised extreme value models. Eur. J. Oper. Res. 249(2), 506\u2013516 (2016)","journal-title":"Eur. J. Oper. Res."},{"issue":"1","key":"29_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"29_CR6","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., Friedman, J. H., and Friedman, J. H.: The elements of statistical learning: data mining, inference, and prediction, Vol. 2. Springer (2009)","DOI":"10.1007\/978-0-387-84858-7"},{"key":"29_CR7","doi-asserted-by":"crossref","unstructured":"James, G., Witten, D., Hastie, T., Tibshirani, R.: An Introduction to Statistical Learning, vol. 112. Springer (2013)","DOI":"10.1007\/978-1-4614-7138-7"},{"key":"29_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113567","volume":"161","author":"M Moscatelli","year":"2020","unstructured":"Moscatelli, M., Parlapiano, F., Narizzano, S., Viggiano, G.: Corporate default forecasting with machine learning. Expert Syst. Appl. 161, 113567 (2020)","journal-title":"Expert Syst. Appl."},{"key":"29_CR9","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1016\/j.eap.2022.03.005","volume":"74","author":"D Zhang","year":"2022","unstructured":"Zhang, D., Sogn-Grundvag, G.: Credit constraints and the severity of Covid-19 impact: empirical evidence from enterprise surveys. Econ. Anal. Policy 74, 337\u2013349 (2022)","journal-title":"Econ. Anal. Policy"}],"container-title":["Smart Innovation, Systems and Technologies","Advanced Neural Artificial Intelligence: Theories and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0994-9_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,23]],"date-time":"2025-05-23T13:23:42Z","timestamp":1748006622000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0994-9_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819609932","9789819609949"],"references-count":9,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0994-9_29","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"type":"print","value":"2190-3018"},{"type":"electronic","value":"2190-3026"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"24 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}