With　the　development　of　electronic　healthcare,　more　and　more　medical　institutions　begin　to　use　the　information　system　to　manage　their　patient＇s　health　records　as　well　as　other　healthcare　data.　Electronic　medical　records　(EMR)　contain　the　patient＇s　personal　information,　medical　history,　clinical　examination,　treatment　process,　and　other　information,　which　have　large　research　value.　Today,　enormous　number　of　electronic　medical　records　accumulated　through　the　hospital　information　system　all　over　the　world.　Analyzing　these　EMRs　can　effectively　assist　doctors　in　clinical　decision-making,　provide　data　support　for　clinical　research　as　well　as　personalized　healthcare　service　for　patients.　This　paper　presents　a　EMR　similarity　computation　system.　The　system　accepts　EMRs　collected　from　hospitals　as　input,　go　through　a　series　of　process,　and　eventually　calculates　the　similarity　of　any　two　EMRs.　An　diseases　classification　experiment　was　designed　to　illustrate　the　effectiveness　of　the　method.　This　system　lays　the　foundation　for　further　analysis　of　electronic　medical　records.