<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-8PHXNTO0</identifier><date>2021</date><creator>Panda, Debjani</creator><relation>documents/doc/8/URN_NBN_SI_doc-8PHXNTO0_001.pdf</relation><relation>documents/doc/8/URN_NBN_SI_doc-8PHXNTO0_001.txt</relation><format format_type="issue">3</format><format format_type="volume">45</format><format format_type="type">article</format><format format_type="extent">str. 381-392</format><identifier identifier_type="ISSN">0350-5596</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID_HOST">97957123</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-8PHXNTO0</identifier><language>eng</language><publisher>Slovensko društvo Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">genetski algoritmi</subject><subject language_type_id="slv">napovedovanje</subject><subject language_type_id="slv">nevronske mreže</subject><subject language_type_id="slv">srčne bolezni</subject><subject language_type_id="slv">strojno učenje</subject><subject language_type_id="slv">umetna inteligenca</subject><title>a novel approach</title><title>Extreme learning machines with feature selection using GA for effective prediction of fetal heart disease</title></Record>