• Safety and Health at Work
• /
• v.2 no.4
• /
• pp.336-347
• /
• 2011

Objectives: In Korea, an average of 258 workers claim compensation for their noise-induced hearing loss (NIHL) on an annual basis. Indeed, hearing disorder ranks first in the number of diagnoses made by occupational medical check-ups. Against this backdrop, this study analyzed the impact of 19 types of noise-generating machines and equipment on the sound pressure levels in workplaces and NIHL occurrence based on a 2009 national survey on work environments. Methods: Through this analysis, a series of statistical models were built to determine posterior probabilities for each worksite with an aim to present risk ratings for noise levels at work. Results: It was found that air compressors and grinding machines came in first and second, respectively in the number of installed noise-generating machines and equipment. However, there was no direct relationship between workplace noise and NIHL among workers since noise-control equipment and protective gear had been in place. By building a logistic regression model and neural network, statistical models were set to identify the influence of the noise-generating machines and equipment on workplace noise levels and NIHL occurrence. Conclusion: This study offered NIHL prevention measures which are fit for the worksites in each risk grade.

• Journal of the Korean Society for Library and Information Science
• /
• v.53 no.4
• /
• pp.171-187
• /
• 2019

The study aims to analyze the posts of depression-related Facebook groups to understand major topics discussed by group users. Specifically, the purpose of the study is to identify the topics and keywords of the posts to understand what users discuss about depression. Depression is a mental disorder that is somewhat sensitive in the online community, which is characterized by accessibility, openness and anonymity. The researchers have implemented a natural language-based data analysis framework that includes components ranging from Facebook data collection to the automated extraction of topics. Using the framework, we collected and analyzed 885 posts created in the past one year from the largest Facebook depression group. To derive more complete and accurate topics, we combined both automated and manual (e.g., stop words removal, topic size determination) methods. Results indicate that users discuss a variety of topics including depression in general, human relations, mood and feeling, depression symptoms, suicide, medical references, family and etc.

• Neurospine
• /
• v.15 no.4
• /
• pp.329-337
• /
• 2018

Objective: Machine learning algorithms excel at leveraging big data to identify complex patterns that can be used to aid in clinical decision-making. The objective of this study is to demonstrate the performance of machine learning models in predicting postoperative complications following anterior cervical discectomy and fusion (ACDF). Methods: Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), and random forest decision tree (RF) models were trained on a multicenter data set of patients undergoing ACDF to predict surgical complications based on readily available patient data. Following training, these models were compared to the predictive capability of American Society of Anesthesiologists (ASA) physical status classification. Results: A total of 20,879 patients were identified as having undergone ACDF. Following exclusion criteria, patients were divided into 14,615 patients for training and 6,264 for testing data sets. ANN and LR consistently outperformed ASA physical status classification in predicting every complication (p < 0.05). The ANN outperformed LR in predicting venous thromboembolism, wound complication, and mortality (p < 0.05). The SVM and RF models were no better than random chance at predicting any of the postoperative complications (p < 0.05). Conclusion: ANN and LR algorithms outperform ASA physical status classification for predicting individual postoperative complications. Additionally, neural networks have greater sensitivity than LR when predicting mortality and wound complications. With the growing size of medical data, the training of machine learning on these large datasets promises to improve risk prognostication, with the ability of continuously learning making them excellent tools in complex clinical scenarios.

• Journal of Korean Neurosurgical Society
• /
• v.62 no.3
• /
• pp.353-360
• /
• 2019

Epilepsy surgery that eliminates the epileptogenic focus or disconnects the epileptic network has the potential to significantly improve seizure control in patients with medically intractable epilepsy. Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) has been an established option for epilepsy surgery since the US Food and Drug Administration cleared the use of MRgLITT in neurosurgery in 2007. MRgLITT is an ablative stereotactic procedure utilizing heat that is converted from laser energy, and the temperature of the tissue is monitored in real-time by MR thermography. Real-time quantitative thermal monitoring enables titration of laser energy for cellular injury, and it also estimates the extent of tissue damage. MRgLITT is applicable for lesion ablation in cases that the epileptogenic foci are localized and/or deep-seated such as in the mesial temporal lobe epilepsy and hypothalamic hamartoma. Seizure-free outcomes after MRgLITT are comparable to those of open surgery in well-selected patients such as those with mesial temporal sclerosis. Particularly in patients with hypothalamic hamartoma. In addition, MRgLITT can also be applied to ablate multiple discrete lesions of focal cortical dysplasia and tuberous sclerosis complex without the need for multiple craniotomies, as well as disconnection surgery such as corpus callosotomy. Careful planning of the target, the optimal trajectory of the laser probe, and the appropriate parameters for energy delivery are paramount to improve the seizure outcome and to reduce the complication caused by the thermal damage to the surrounding critical structures.

• Journal of Hospice and Palliative Care
• /
• v.22 no.3
• /
• pp.117-124
• /
• 2019

A resolution adopted by the World Health Assembly in 2014 stated that all nurses should be equipped with palliative care skills in order to integrate palliative care into a day-to-day healthcare system. This article introduces the palliative nursing competency that was developed for the Korean environment by the Korean Hospice Palliative Nursing Research Network based on its study of overseas cases where this competency and competency-based training were developed. This is the first step towards the development of competency-based palliative nursing education, and active efforts should be made to integrate this competency into the undergraduate nursing curriculum.

• Healthcare Informatics Research
• /
• v.24 no.4
• /
• pp.253-262
• /
• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.2
• /
• pp.215-222
• /
• 2019

Advances in technologies about 3D (three-dimensional) printing and smart factory related issues will have the effect of reducing the cost of building a smart factory and making various types of service available. Manufacturers and service providers of small assets work with outside experts to provide small amounts of customized ordering services. If customers have to disclose their private information to subscribe to a new service, they may be reluctant to use it and the availability of developed technology may cause slow progress. We propose a new protocol for customized order service for smart factory. The proposed approach is designed to meet requirements of security and based on smart contract in IoT convergence network. We analyzed the requirements of the proposed approach which provided anonymity, privacy, fairness, and non-repudiation. We compared it with closely related studies to show originality and differences.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.11
• /
• pp.1420-1427
• /
• 2019

Super aged society, Japan actively uses Information Communication Technology(ICT) as one of solving methods for various social problem. Especially, for Korea where soon will become super aged society, it would be meaningful to examine the current policy trends and utilization of senior support using ICT in Japan. This study explores the policy trends and utilization of senior support using ICT in Japan through literature review, and then proposes some suggestions as follows. Opportunities for practical use of ICT should be widened in the field of senior support, and efforts are needed to build an information linkage network between institutions for senior support because linkage between care sector and medical sector is important for the elderly support. Besides, simplification of paperwork and easing of burden of care providers or workers in the field should be sought by development and dissemination of various robots. Moreover, the spread of technology for emotional support and stability should be actively pursued by using ICT.

• Journal of Platform Technology
• /
• v.8 no.3
• /
• pp.3-9
• /
• 2020

As the need for sharing for research purposes in the medical field increases, the use of a Common Data Model (CDM) is increasing. However, when sharing CDM data, there are some problems in that access control and personal information in the data are not protected. In this paper, in order to solve this problem, access to CDM data is controlled by using an encryption method in a blockchain network, and information of CDM data is recorded to enable tracking. In addition, IPFS was used to share a large amount of CDM data, and Celery was used to automate the sharing process. In other words, we propose a multi-channel automation system in which the information required for CDM data sharing is shared by a trust-based technology, a distributed file system, and a message queue for automation. This aims to solve the problem of access control and personal information protection in the data that occur in the process of sharing CDM data.

• Parasites, Hosts and Diseases
• /
• v.59 no.1
• /
• pp.103-108
• /
• 2021

To date, there is no report on the genetic diversity of ticks in these regions. A total of 370 representative ticks from the south and east regions of Kazakhstan (SERK) and Xinjiang Uygur Autonomous Region (XUAR) were selected for molecular comparison. A fragment of the mitochondrial cytochrome c oxidase subunit I (cox1) gene, ranging from 631 bp to 889 bp, was used to analyze genetic diversity among these ticks. Phylogenetic analyses indicated 7 tick species including Hyalomma asiaticum, Hyalomma detritum, Hyalomma anatolicum, Dermacentor marginatus, Rhipicephalus sanguineus, Rhipicephalus turanicus and Haemaphysalis erinacei from the SERK clustered together with conspecific ticks from the XUAR. The network diagram of haplotypes showed that i) Hy. asiaticum from Almaty and Kyzylorda Oblasts together with that from Yuli County of XUAR constituted haplogroup H-2, and the lineage from Chimkent City of South Kazakhstan was newly evolved; and ii) the R. turanicus ticks sampled in Israel, Almaty, South Kazakhstan, Usu City, Ulugqat and Baicheng Counties of XUAR were derivated from an old lineage in Alataw City of XUAR. These findings indicate that: i) Hy. asiaticum, R. turanicus and Ha. erinacei shared genetic similarities between the SERK and XUAR; and ii) Hy. marginatum and D. reticulatus show differences in their evolution.