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                <identifier>ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai:2:11827</identifier>
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                    <dim:field mdschema="dc" element="title" lang="en">Machine learning model for financial forecasting using the military healthcare as an example</dim:field>
                    <dim:field mdschema="dc" element="date" qualifier="issued">2025</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="uri">http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/2/11827</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="uri">https://akademski-pregled.ubn.rs.ba/index.php/ap/issue/view/14/14</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="id:54769" confidence="-1">I. Đorić</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="etfid:191" confidence="-1">M. Milojević</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="id:54771" confidence="-1">S. Zurovac</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="id:54772" confidence="-1">M. Ranisavljević</dim:field>
                    <dim:field mdschema="dc" element="contributor" qualifier="author" authority="orcid::0000-0001-5415-6746" confidence="-1">N. Radović</dim:field>
                    <dim:field mdschema="dc" element="description" qualifier="abstract">Predicting  future  events  through  the  analysis  of  historical  data  poses  a  challenge  for decision  makers.  In  this  paper,  the  authors  investigate  the  possibility  of  machine learning  application  by  solving  a  regression  problem  for  prediction  from  time  series data of the military healthcare costs in the Republic of Serbia. The present research aims to determine the possibilities of using artificial intelligence in financial forecasting, as well as to select, based on the research results, the most reliable modelwhich, taking into account the  relationships  between the historical data of the planning subject and the market economic conditions in the observed period, will provide relevant data for future decisions.</dim:field>
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                    <dim:field mdschema="dc" element="citation" qualifier="epage">202</dim:field>
                    <dim:field mdschema="dc" element="identifier" qualifier="issn">2637-2525</dim:field>
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