{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T15:40:34Z","timestamp":1743090034222,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":12,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811648830"},{"type":"electronic","value":"9789811648847"}],"license":[{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-16-4884-7_22","type":"book-chapter","created":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T09:03:43Z","timestamp":1635411823000},"page":"271-281","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Detecting Autism Spectrum Disorder Using Data Mining"],"prefix":"10.1007","author":[{"given":"Ana C.","family":"Guisasola","sequence":"first","affiliation":[]},{"given":"Diana","family":"Ferreira","sequence":"additional","affiliation":[]},{"given":"Cristiana","family":"Neto","sequence":"additional","affiliation":[]},{"given":"Ant\u00f3nio","family":"Abelha","sequence":"additional","affiliation":[]},{"given":"Jos\u00e9","family":"Machado","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,10,29]]},"reference":[{"issue":"7","key":"22_CR1","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1001\/archpedi.157.7.622","volume":"157","author":"JG Gurney","year":"2003","unstructured":"Gurney, J.G., Fritz, M.S., Ness, K.K., Sievers, P., Newschaffer, C.J., Shapiro, E.G.: Analysis of prevalence trends of autism spectrum disorder in Minnesota. Arch. Pediatr. Adoles. Med. 157(7), 622\u2013627 (2003)","journal-title":"Arch. Pediatr. Adoles. Med."},{"issue":"5","key":"22_CR2","first-page":"583","volume":"18","author":"AM Daniels","year":"2014","unstructured":"Daniels, A.M., Mandell, S.D.: Explaining differences in age at autism spectrum disorder diagnosis: a critical review. Austism 18(5), 583\u2013597 (2014)","journal-title":"Austism"},{"issue":"6","key":"22_CR3","first-page":"7288","volume":"5","author":"MS Mythili","year":"2014","unstructured":"Mythili, M.S., Shanavas, A.M.: A novel approach to predict the learning skills of autistic children using SVM and decision tree. Int. J. Comput. Sci. Inf. Technol. 5(6), 7288\u20137291 (2014)","journal-title":"Int. J. Comput. Sci. Inf. Technol."},{"key":"22_CR4","unstructured":"Leroy, G.A., Irmscher, A., Charlop, M.H.: Data mining techniques to study therapy success with autistic children (2006)"},{"issue":"4","key":"22_CR5","doi-asserted-by":"publisher","first-page":"2431","DOI":"10.1007\/s10916-011-9710-5","volume":"36","author":"I Yoo","year":"2012","unstructured":"Yoo, I., Alafaireet, P., Marinov, M., Pena-Hernandez, K., Gopidi, R., Chang, J., Hua, L.: Data mining in healthcare and biomedicine: a survey of the literature. J. Med. Syst. 36(4), 2431\u20132448 (2012)","journal-title":"J. Med. Syst."},{"issue":"16","key":"22_CR6","doi-asserted-by":"publisher","first-page":"5510","DOI":"10.3390\/app10165510","volume":"10","author":"D Ferreira","year":"2020","unstructured":"Ferreira, D., Silva, S., Abelha, A., Machado, J.: Recommendation system using autoencoders. Appl. Sci. 10(16), 5510 (2020)","journal-title":"Appl. Sci."},{"key":"22_CR7","doi-asserted-by":"crossref","unstructured":"Omar, K.S., Mondal, P., Khan, N.S., Rizvi, M.R.K., Islam, M.N.: A machine learning approach to predict autism spectrum disorder. In: 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE), pp. 1\u20136. IEEE Press, New York (2019)","DOI":"10.1109\/ECACE.2019.8679454"},{"key":"22_CR8","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1016\/j.procs.2020.03.399","volume":"167","author":"S Raj","year":"2020","unstructured":"Raj, S., Masood, S.: Analysis and detection of autism spectrum disorder using machine learning techniques. Procedia Comput. Sci. 167, 994\u20131004 (2020)","journal-title":"Procedia Comput. Sci."},{"issue":"1","key":"22_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-020-01682-8","volume":"45","author":"B Martins","year":"2021","unstructured":"Martins, B., Ferreira, D., Neto, C., Abelha, A., Machado, J.: Data mining for cardiovascular disease prediction. J. Med. Syst. 45(1), 1\u20138 (2021)","journal-title":"J. Med. Syst."},{"key":"22_CR10","unstructured":"Wirth, R., Hipp J.: CRISP-DM. In: Towards a Standard Process Model for Data Mining, pp. 29\u201339. Springer-Verlag, London, UK (2000)"},{"key":"22_CR11","unstructured":"UCI machine learning repository: autism screening adult data set. https:\/\/archive.ics.uci.edu\/ml\/datasets\/AutismScreeningAdult"},{"issue":"1","key":"22_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-020-01686-4","volume":"45","author":"C Neto","year":"2021","unstructured":"Neto, C., Senra, F., Leite, J., Rei, N., Rodrigues, R., Ferreira, D., Machado, J.: Different scenarios for the prediction of hospital readmission of diabetic patients. J. Med. Syst. 45(1), 1\u20139 (2021)","journal-title":"J. Med. Syst."}],"container-title":["Smart Innovation, Systems and Technologies","Developments and Advances in Defense and Security"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-4884-7_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,28]],"date-time":"2021-10-28T09:06:59Z","timestamp":1635412019000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-4884-7_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,29]]},"ISBN":["9789811648830","9789811648847"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-4884-7_22","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"type":"print","value":"2190-3018"},{"type":"electronic","value":"2190-3026"}],"subject":[],"published":{"date-parts":[[2021,10,29]]},"assertion":[{"value":"29 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}