A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td class="align_left">Cluster</td><td class="align_center">1</td><td class="align_center">2</td><td class="align_center">3</td><td class="align_center">4</td><td class="align_center">Valid</td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td class="align_left">Cases</td><td class="align_center">19083</td><td class="align_center">32116</td><td class="align_center">19725</td><td class="align_center">1162</td><td class="align_center">72086</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Number of cases in each of the clusters (surgical patients).

International Journal of Telemedicine and Applications

tab5

Table 5

Table 5: A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment 