Soo-Yong Shin 교수

Despite the growing adoption of the mobile health (mHealth) applications (apps), few studies address concerns with low retention rates. This study aimed to investigate how the usage patterns of mHealth app functions affect user retention. We collected individual usage logs for 1,439 users of single tethered personal health record app, which spanned an 18-months period from August 2011 to January 2013. The user logs contained timestamps whenever an individual uses each function, which enables us

The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter d

FL demonstrated comparative performance on different benchmark datasets. In addition, FL demonstrated reliable performance in cases where the distribution was imbalanced, skewed, and extreme, reflecting the real-life scenario in which data distributions from various hospitals are different. FL can achieve high performance while maintaining privacy protection because there is no requirement to centralize the data.

De-identification of personal health information is essential in order not to require written patient informed consent. Previous de-identification methods were proposed using natural language processing technology in order to remove the identifiers in clinical narrative text, although these methods only focused on narrative text written in English. In this study, we propose a regular expression-based de-identification method used to address bilingual clinical records written in Korean and Englis

Molecular programming (MP) has been proposed as an evolutionary computation algorithm at the molecular level (B.T. Zhang and S.Y. Shin, 1998). MP is different from other evolutionary algorithms in its representation of solutions using DNA molecular structures and its use of bio-lab techniques for recombination of partial solutions. Molecular programming is applied to traveling salesman problems (TSPs) whose solution requires encoding of real values in DNA strands. We propose a new encoding schem

Since DNA computing technologies use the bio-molecules as basic computing materials, DNA computing involves the possibilities for errors caused by the chemical characteristics of bio-molecules. To overcome these drawbacks, many researchers have studied the design of DNA sequences to reduce the possibilities for illegal reactions. We developed an evolutionary sequence generation system to minimize the potential errors in DNA sequences for reliable DNA computing. We verified our system by investig

of a DW is a dedicated computer system or database that consolidates subject-oriented, time-variant, and non-volatile data from multiple sources to support decision-making processes. Recently, DWs have become invaluable resources in various domains, and they are used to analyze trends over time or to extract valuable information.

We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly.

Recently, digital health has gained the attention of physicians, patients, and healthcare industries. Digital health, a broad umbrella term, can be defined as an emerging health area that uses brand new digital or medical technologies involving genomics, big data, wearables, mobile applications, and artificial intelligence. Digital health has been highlighted as a way of realizing precision medicine, and in addition is expected to become synonymous with health itself with the rapid digitization

Our study shows that mobile search queries for influenza surveillance have equaled or even become greater than desktop search queries over time. In the future development of influenza surveillance using search queries, the recognition of changing trend of mobile search data could be necessary.

Smartphones have been widely used recently to monitor heart rate and activity, since they have the necessary processing power, non-invasive and cost-effective sensors, and wireless communication capabilities. Consequently, healthcare applications (apps) using smartphone-based sensors have been highlighted for non-invasive physiological monitoring. In addition, several healthcare apps have received FDA clearance. However, in spite of their potential, healthcare apps with smartphone-based sensors

Recently many researchers have studied the estimation of distribution algorithms (EDAs) as an optimization method. While most EDAs focus on solving combinatorial optimization problems, only a few algorithms have been proposed for continuous function optimization. In previous work, we developed a Bayesian evolutionary algorithm (BEA) for combinatorial optimization problems using a probabilistic graphical model known as a Helmholtz machine. Since BEA is a general framework for evolutionary computa

FL in the medical domain appears to be in its early stages, with most research using open data and focusing on specific data types and diseases for performance verification purposes. Nonetheless, medical FL research is anticipated to be increasingly applied and to become a vital component of multi-institutional research.