%0 Journal Article %1 rahman2009emantic %A Rahman, A Asmita %A Arpinar, B Budak %A Sundar, C Singaram %D 2009 %K Matchmaking Matchmaking, Semantic algorithm %T Semantic Discovery and Retrieval of Relevant Medical Knowledge %X - In the fast growing world of information, the regimen of Mr. Burton as it puts him in high-risk category for

@article{rahman2009emantic, abstract = {- In the fast growing world of information, the regimen of Mr. Burton as it puts him in high-risk category for }, added-at = {2015-01-14T21:25:14.000+0100}, author = {Rahman, A Asmita and Arpinar, B Budak and Sundar, C Singaram}, biburl = {https://www.bibsonomy.org/bibtex/2c9925a18fe0ca9787046a2466ddfa24c/diverzulu}, file = {:D\:\\ASUS-FINO\\Inkhognito_M\\David\\PhD\\Web Semântica\\Biomedicine Ontology\\Automated Acquisition\\2012-SWW-Semantic Discovery and Retrieval of Relevant Medical Knowledge.pdf:PDF}, interhash = {430410030b5fbe3f54ed13c1519f1d19}, intrahash = {c9925a18fe0ca9787046a2466ddfa24c}, keywords = {Matchmaking Matchmaking, Semantic algorithm}, review = {Semantic Discovery and Retrieval of Relevant Medical Knowledge 1 1 A. 1Asmita Rahman , B. Budak Arpinar , and C. Singaram Sundar 1 Computer Science Department, University of Georgia, Athens, Georgia, USA 30602 This research finding has direct implication on the treatment Abstract - In the fast growing world of information, the regimen of Mr. Burton as it puts him in high-risk category for amount of medical knowledge is growing at an exponential a second heart attack. Currently, there are a few ways in level. It has now become a very difficult task for an ordinary which Dr. Brown can learn about the discovery: (a) searching person to keep up with all the new discoveries and updates in and browsing relevant web sites (e.g., PubMed); (b) attending this domain. This paper describes an approach to a conference/ professional meeting where recent research semantically discover and retrieve relevant medical findings are discussed; or (c) through colleagues who may data/information for respective health records (people). This have knowledge about the new discoveries. However, in all of system comprises of sample Electronic Health Records these methods, there could be significant delays between (EHRs) and Health Publications from PubMed. Our system publishing of new information and Dr. Brown becoming implements a semantic matchmaking algorithm to find the aware of the information. Even after Dr. Brown becomes relevant publications in PubMed for any particular health aware of the study, his staff has to search through patients’ record (profile) using BioPortal Ontologies and UMLS. It medical records to identify the patients who are on Plavix and then displays the results to the user. Our system empowers the Prilosec simultaneously which can be difficult process [20]. users and enables them to discover hidden but relevant Here is the diagram that illustrates this scenario: information. The result of the evaluation clearly proves that our system retrieves the relevant information better than syntactic searches. Keywords: Semantic Matchmaking, Matchmaking algorithm, Knowledge Discovery, Electronic Health Records, Health Publications, Ontology. 1 Introduction We all know that today the knowledge in the medical domain is growing at a very fast pace. It is becoming harder and almost impossible for a normal person to keep up with all the updates in this field. Every day there are several new drugs coming to market, several new treatment options are being introduced, many old medications are being replaced, several new discoveries are being made etc. In this fast moving world, there is barely any time left for a normal Figure 1: Test case scenario diagram. person to read and research about the new updates in the medical industry. Our research is going to contribute in this Since the matchmaking in our system is done on the field by making relevant information easily available. semantics rather than the syntax, the knowledge discovery enables the system to find such relevant publications and 1.1 Motivating Scenario provide the results to the patient. Mr. Burton is a patient of Dr. Brown. Mr. Burton has 2 Related Work had a heart attack in 2005. Dr. Brown has prescribed the drug Plavix to reduce the risk of future heart attacks. As Plavix Related works include research done in the field of health leads to acid reflux, the doctor has also prescribed the drug and science for clinical trials. It also includes researches that Prilosec to lower acidity. Note that until recently this has been use semantic graphs and relationships for retrieval of the standard treatment regimen for patients with heart attack information. histories. In March 2009, a study appeared in the Journal of American Medical Association, which indicated that TrialX: It is a system, a third party tool that is built for combination of drugs Clopidogrel (Plavix is the brand name recruiting related health records for clinical trials. As one must of Clopidogrel) and proton pump inhibitor (PPI) Prilosec is realize that before any medication becomes available to the one of the PPIs) in patients with previous histories of heart market, there are clinical trials performed to measure the attacks can actually double the risk of second heart attack. e fficiency and side effects of the same. However, this process}, timestamp = {2015-01-14T21:25:14.000+0100}, title = {Semantic Discovery and Retrieval of Relevant Medical Knowledge}, year = 2009 }