{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T18:59:07Z","timestamp":1648666747759},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,9,15]]},"abstract":"<jats:p>Deep learning has recently gained the attention of many researchers in various fields. A new and emerging machine learning technique, it is derived from a neural network algorithm capable of analysing unstructured datasets without supervision. This study compared the effectiveness of the deep learning (DL) model vs. a hybrid deep learning (HDL) model integrated with a hybrid parameterisation model in handling complex and missing medical datasets as well as their performance in increasing classification. The results showed that 1) the DL model performed better on its own, 2) DL was able to analyse complex medical datasets even with missing data values, and 3) HDL performed well as well and had faster processing times since it was integrated with a hybrid parameterisation model.<\/jats:p>","DOI":"10.3233\/faia200551","type":"book-chapter","created":{"date-parts":[[2020,9,17]],"date-time":"2020-09-17T13:24:23Z","timestamp":1600349063000},"source":"Crossref","is-referenced-by-count":0,"title":["Effectiveness of a Hybrid Deep Learning Model Integrated with a Hybrid Parameterisation Model in Decision-Making Analysis"],"prefix":"10.3233","author":[{"given":"Masurah","family":"Mohamad","sequence":"first","affiliation":[{"name":"Faculty of Engineering, Universiti Teknologi Malaysia & Media and Game Innovation Centre of Excellence (MaGICX), Universiti Teknologi Malaysia, 81310 Johor Baharu, Johor, Malaysia"},{"name":"Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perak Branch, Tapah Campus, Tapah Road, 35400 Perak, Malaysia"}]},{"given":"Ali","family":"Selamat","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Universiti Teknologi Malaysia & Media and Game Innovation Centre of Excellence (MaGICX), Universiti Teknologi Malaysia, 81310 Johor Baharu, Johor, Malaysia"},{"name":"Malaysia Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur, Malaysia"},{"name":"University of Hradec Kralove, Rokitanskeho 62, 500 03 Hradec Kralove, Czech Republic"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Knowledge Innovation Through Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"http:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA200551","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,17]],"date-time":"2020-09-17T13:24:23Z","timestamp":1600349063000},"score":1,"resource":{"primary":{"URL":"http:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA200551"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,15]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia200551","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,15]]}}}