Medical　search　technologies　are　crucial　to　enable　the　user　to　rapidly　and　effectively　discover　useful　information　from　massive　medical　and　clinical　data.　Because　of　the　complexity　of　medical　terminology,　traditional　information　search　methods　have　not　fully　expressed　the　intention　of　the　query　request　and　explored　the　potential　semantic　knowledge　in　the　document.　In　this　paper,　we　propose　a　multi-analysis　approach　by　considering　the　medical　ontology　as　a　semantic　resource,　which　can　excavate　latent　semantic　information　of　a　user＇s　query　request.　In　addition,　we　also　recognize　topics　of　medical　documents　to　express　text　contents　for　providing　support　for　calculating　the　similarity　between　query　keywords　and　documents.　Our　experiments　on　PubMed　medical　article　collections　show　that　the　semantic-based　multi-analysis　approach　is　feasible　and　efficient　compared　with　other　traditional　approaches　in　medical　retrieval.