<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-Z742C06M</identifier><date>2023</date><creator>Chegireddy, Rama Prakasha Reddy</creator><creator>SriNagesh, A</creator><relation>documents/doc/Z/URN_NBN_SI_doc-Z742C06M_001.pdf</relation><relation>documents/doc/Z/URN_NBN_SI_doc-Z742C06M_001.txt</relation><format format_type="issue">1</format><format format_type="volume">47</format><format format_type="type">article</format><format format_type="extent">str. 115-129</format><identifier identifier_type="ISSN">0350-5596</identifier><identifier identifier_type="DOI">10.31449/inf.v47i1.4433</identifier><identifier identifier_type="COBISSID">196214275</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-Z742C06M</identifier><language>eng</language><publisher publisher_location="Ljubljana">Slovene Society Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">globoko učenje</subject><subject language_type_id="slv">ledvice</subject><subject language_type_id="slv">rak (medicina)</subject><subject language_type_id="slv">umetna inteligenca</subject><title>A novel method for human MRI based pancreatic cancer prediction using integration of Harris Hawks varients &amp; VGG16: a deep learning approach</title></Record>