• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.1-14
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• 2019

The names of medical technologist in Korea, Japan, and the United State of America vary depending on the medical system, educational system, and work areas. Conventionally, jobs equal or similar to medical technologist (commonly known as clinical laboratory technologist, medical laboratory technologist, clinical laboratory scientist, and medical laboratory scientist), histotechnologist, cytotechnologist, and genetic technologist. Jobs, such as extracorporeal technologist, medical electrophysiology technologist, and medical sonographer, allow other allied health professionals including medical technologists, to obtain their qualification. The work areas of medical technologists are classified into clinical pathologic technology, pathologic technology, clinical genetics technology, nuclear medicine in vitro technology, and clinical physiologic technology. New titles of Korean specialized medical technologists refer to certification systems, such as CLMJ, CMAJ, ASCP, IAC, ABRET, and ARMDS. Currently, there are eight types of specialized medical technologists under the cooperation of specialized academic societies. They are hematology, transfusionology, chemistry, immunology, microbiology, histology, cytology, nuclear medicine. It can be further divided into 20 categories according to the work areas such as mass spectrometry, infection control, Pathologists' Assistant, flow cytometry, HLA, cytogenetics, molecular genetics, cardiopulmonary physiology, neurophysiology (EEG/EMG/PSG/etc.), cardiac sonography, neurosonography (TCD/carotid), and medical device quality manager.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.2
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• pp.55-68
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• 2017

In recent years, medical practice has seen a drastic change due to the rapid, exponential expansion of scientific and medical technologies. Specially, the role of medical technologists (also known as medical laboratory scientists and/or clinical laboratory scientists) are increasing in the development of science of medical technology. As such, their responsibility has also been increasing. Therefore, given their highly specialized knowledge and skills, they are not regarded solely as doctor's assistants. Their independence and deeper specialization have been increasing, as they perform medial practices under the guidance of doctors or dentists pursuant to the "Act on Medical Service Technologists." From a legal point of view, medical guidance and scope of work were examined. As a conclusion, the definition of doctor's superintendency on the "Act on Medical Service Technologists" is required, and the qualification for the Korean license examination and their roles should be stated clearly. Moreover, communications among health professions regarding the roles of medical technologists are necessary to further facilitate clarification of their role. There is a need for independent legislation to expand the field of medical technologists and to strengthen their professionalism.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.1
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• pp.83-89
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• 2020

There is a noticeable gap in the personnel structures of clinical laboratories between North Korea and South Korea. In North Korea, 'Laboratory Doctor' is similar to the workforce of 'Medical Technologist (commonly known as Clinical Laboratory Technologist or Medical Laboratory Scientist)' in South Korea. Considering preceding research based on the verbal evidence of North Korean healthcare personnel defectors, it is estimated that the status of laboratory doctor in North Korea generally corresponds to physician and feldsher (such as physician assistant in Western countries). Physicians and feldshers are trained and fostered for five and a half years in medical universities and for three years in medical vocational schools (so-called junior college of medicine). Unlike South Korea, the North Korea's healthcare personnel system does not subdivide the tasks, education, qualifications and law regarding the specialties of health experts. It is thought that the Korean Association of Medical Technologists needs to collaboratively search and present the milestones for establishment of a professional system on clinical laboratory personnel in North Korea through cooperative research on policies with the related organizations for better preparation of the unification of the Korean Peninsula.

• Toxicological Research
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• v.33 no.3
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• pp.205-209
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• 2017

Transmembrane Protein 39A (TMEM39A) is a member of TMEM family. The understanding about this protein is still limited. The earlier studies indicated that TMEM39A was a key mediator of autoimmune disease. TMEM39A seems to be involved in systemic lupus erythematosus and multiple sclerosis in numerous of populations. All of these works stop at insufficient information by using gene functioning methods such as: Genome-wide association studies (GWASs) and/or follow-up study. It is the fact that the less understood of TMEM39A actually is the attraction to the scientist in near future. In this review the current knowledge about TMEM39A and its possible roles in cell biology, physiology and pathology will be described.

• Korean Journal of Clinical Laboratory Science
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• v.53 no.1
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• pp.105-121
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• 2021

To investigate and accommodate opinions on the revision of the official occupational title of the medical technologist, the Korean Association of Medical Technologists (KAMT) requested 22,638 people registered as its regular members to participate in an online survey and select their two preferred options from the alternative job titles presented. Survey responses were collected from 3,999 people (17.66%). To examine job title preferences among the KAMT members, each respondent was asked to choose two terms from the choice set. As a result, 6,958 responses were obtained, and out of the total responses, 5,555 (79.83%) indicated a choice for a job title that included the word 'analyst' as the preferred alternative. The survey results showed that "Diagnostic Laboratory Analyst" was the most preferred alternative selected by the largest proportion of respondents (2,417 responses, 34.73%), followed by "Clinical Laboratory Analyst" (1,710 responses, 24.57%), "Biomedical Pathology Technologist" (758 responses, 10.89%), "Biomedical Analyst" (730 responses, 10.49%), "Biomedical Laboratory Analyst" (730 responses, 10.03%), and "Clinical Laboratory Scientist" (646 responses, 9.26%). Therefore, based on the responses of the surveyed members, results of consultation and literature review, the Standard Classification of Occupations (SCO), and the current status of the job titles used in major countries, it is suggested that the occupational title of medical technologists should be changed by adopting "Diagnostic Laboratory Analyst", "Biomedical Laboratory Analyst", or "Biomedical Analyst" as their new official job title.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.4
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• pp.495-503
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• 2019

This study explored the method of determining the appropriate size of the workforce according to the assessment of the workload of medical technologists (also called medical and clinical laboratory technologists, and medical and clinical laboratory scientists) in order to present a standard production model for the appropriate manpower in blood collection rooms. The eleven university hospitals selected for this study had between 600 and 2,000 beds. The 14-steps standard blood collection time was 4 minutes and 8 seconds for the outpatients aged between 20 to 60 years old (57%) except for children and the elderly (43%). Assuming that there were 8 hours per day for mechanically collecting blood, the maximum number of blood donations by one clinical laboratory scientist was analyzed to be 100 cases. In conclusion, it is appropriate to have fewer than 100 cases of daily blood collection by a medical technologist engaged in blood collection. Since the proper number of blood collection workers (100% of blood collection work)=the number of annual working days/(one day's work hours/time per case)×the number of working days per year, then the proper number of blood collection workers (one day's work hours)=the number of working days per year/100×the number of working days).

• Proceedings of the KSRS Conference
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• v.2
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• pp.627-630
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.