Many of CCADD members have attended the Spring Conference of The Korean Society of Medical Informatics (KOSMI), held at Samsung Medical Comprehensive Cancer Center on June 14-15, 2018. Reflecting the recent drastic increase in the demand and importance of data science in health sciences, the theme of the conference was 'Evolving Data for Better Health'. More than 600 researchers, practitioners, and vendors in health informatics gathered together to share their knowledge, experience, results of research, and expertise through a series of keynote speeches, symposia, oral/poster presentations, and exhibitions.
Four abstracts by CCADD were accepted for poster presentation. Yoomin Jeon proposed a new approach to transform clinical trials eligibility criteria (EC, free-text) into structured data using the OMOP-CDM(Feasibility of Using the OMOP Common Data Model to Assess Clinical Trial Feasibility). She found that >75% of the EC could be mapped by the proposed approach, and the most important data group was condition.
Serin Lee, a student intern, gave her poster presentation entitled 'Dimensionality Reduction Model for Common Eligibility Criteria to effectively use Electronic Medical Record: A Pilot Study.' She proposed a dimensionality reduction model for common eligibility features (CEFs) based on ontology and semantic features of EC to reasonably compose the concept sets.
Dr. Soohyun Kim proposed a new type of command data model for clinical trials (Clinical Trial Common Data Model, CT-CDM) to support decision-making processes in clinical trials, entitled 'CDISC-based Common Data Model for Developing an Integrated Decision-Support System in Clinical Trials'. This command data model fully complies with the standards of Clinical Data Interchange Standards Consortium(CDISC) as a global, platform-independent data standard guaranteeing system interoperability.
Lastly, but not the least, Dr. Jeong-An Gim shared his research findings: Application of Machine Learning Technology to Classify Healthy Subjects into Different Pharmacokinetic Exposure Groups to Tacrolimus. Using the decision-tree approach employed in R, Dr. Gim aimed to identify SNPs that are associated with the exposure to tacrolimus. The rs776746 in the CYP3A5 gene was the most influential mutation.
More detailed research findings can be downloaded below.
Much to everyone's delighted surprise, Serin Lee won an external solid-state drive of 1TB at the raffle draw! Since Serin will graduate in August, the prize was certainly a nice present.
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