Purpose: We propose the Lifelog Bigdata Platform as a sustainable digital healthcare system based on individual-centric lifelog datasets and describe the standardization of lifelog and clinical data in its full-cycle management system. Materials and Methods: The Lifelog Bigdata Platform was developed by Yonsei Wonju Health System on the cloud to support digital healthcare and precision medicine. It consists of five core components: data acquisition system, de-identification of individual information, lifelog integration, analyzer, and service. We designed a gathering system into a dedicated virtual machine to save lifelog or clinical outcomes and established standard guidelines for maintaining the quality of gathering procedures. We used standard integration keys to integrate the lifelog and clinical data. Metadata were generated from the data warehouse after loading combined or fragmented data on it. We analyzed the de-identified lifelog and clinical data using the lifelog analyzer to prevent and manage acute and chronic diseases through providing results of statistics on analysis. Results: The big data centers were built in four hospitals and seven companies for integrating lifelog and clinical data to develop the Lifelog Bigdata Platform. We integrated and loaded lifelog big data and clinical data for 3 years. In the first year, we uploaded 94 types of data on the platform with a total capacity of 221 GB. Conclusion The Lifelog Bigdata Platform is the first to combine lifelog and clinical data. The proposed standardization guidelines can be used for future platforms to achieve a virtuous cycle structure of lifelogging big data and an industrial ecosystem.

Background: Healthcare works are high risk of infection through occupational exposure that contact with blood and other body fluids, including infected person, uses needles, syringes, equipment or exposures to sharp instruments. The World Health Organization (WHO) estimates, approximately 66,000 health workers are infected with the hepatitis B virus (HBV) and 200-5000 workers arc infected with human immunodeficiency virus (HIV) each year due to carelessness. HBV infection is a global health problem that remains to preventive. Hepatitis B can be prevented by vaccines that are safe, available and effective. In our country, which has a high prevalence of hepatitis B virus infection, it has been concluded that the coverage of hepatitis B vaccination and the level of immunity of health workers are insufficient. Aim: To evaluate post vaccination immunity against HBV in the staff of National center for transfusion medicine Methods: 63 workers with negative surface antigen of hepatitis B (HBsAg) and absent anamnesis of infection were selected for this study. In 2019 and 2020 all 63 workers were evaluated post vaccination immunity against HBV. Analysis done by Sysmex HSCL800 that is an automated immune assay system. Results and discussion: This center was begun to conduct the vaccination of workers from 2011. Among total 63 individuals involved in this study 53 (84.1%) were vaccinated against hepatitis B and 10 (15.9%) were not vaccinated. From the vaccinated 53 workers, 47 (88,7%) have immunized (anti-H Bs > 1 Ou/ml) but 6 (11.3%) of them were not immunized (anti-HBs <1 Ou/ml).
Therefore 1(1,9%) worker of them received just first dose, 14 (26.4%) workers were injected second dose, whereas 38 (71.7%) workers were vaccinated with third dose. The study shows that 12 (85.7%) workers after second dose and 34 (89.5%) workers after third dose were immunized. Conclutions As a result of hepatitis B vaccination, 88.7% of workers of the NCTM have had immunized against HBV. The final evaluation shows that 36 (57%) of workers had stable, 17 (27%) increased, and 10(16%) decreased level of immunization than the previous year.

Background: Establishment of quantitative reference intervals of white blood cells and its subpopulations using a high accuracy analytic system is essential for clinical medicine, public health, and anthropology. We are unable to identify peer-reviewed literature sources describing white blood cell counts and their subpopulations using monoclonal antibodies to specific surface antigens in healthy Mongolians. This study aimed to measure the counts of white blood cells and their subpopulations in healthy Mongolians using flowcytometry. Materials and Methods: The absolute number (cell/L) of leukocytes (CD45+), granulocytes, monocytes and lymphocytes were measured by Magnetic Activated Cell Sorting Assay (MACSQuant Analyzer 10) in 287 blood donors (158 males and 129 females) 17-64 years of age (mean age 33.1±12.4). Peripheral blood samples were collected at the time of blood donation at the National Center for Transfusion Medicine. Results The mean values of leukocytes and granulocytes were lower in donors over 30 years of age (ANOVA: F=4.408, p=0.002 and F=5.685, p=0.001) and regression analysis demonstrated indirect correlation between counts of these cells and age of donors (r= - 0.198, p=0.001 and r=-0.221, p=0.001, respectively). Gender-related differences in white blood cell counts were not found.
Mean value of lymphocyte count in donors investigated in spring (May and March, n = 87; 2224.6±775.3) was significantly higher than those in winter (December – February, n=180; 1613.2±454.3, p=0.001) and autumn (October, n=20; 1576.1±438.6, p= 0.001).
Comparing of our findings with the data from available literature shown that healthy Mongolians have lower leukocyte count compared with Koreans, Chinese Han population and lower mean value of lymphocyte count comparing with Korean, Chinese Han population, and Arabian (Saudi Arabia) populations.

Background: A blood product is any therapeutic substance derived from human blood, including whole blood and other blood components for transfusion, and plasma-derived medicinal products. Medicinal (medical therapeutic) products derived from human donations of blood and plasma play a critical role in health care. Safe, effective and quality-assured blood products contribute to improving and saving millions of lives every year, as they: address child mortality and maternal health, dramatically improve the life expectancy and quality of life of patients suffering from life-threatening inherited disorders, such as haemophilia, thalassaemia and immune deficiency, and acquired conditions such as cancer and traumatic haemorrhage and support complex medical and surgical procedures, including transplantation. An insufficient or unsafe blood supply for transfusion has a negative impact on the effectiveness of key health services and programmes to provide appropriate patient care in numerous acute and chronic conditions. Ensuring access of all patients who require transfusion to safe, effective and quality-assured blood products is a key component of an effective health system and vital for patient safety.
Although the number of blood donors is increasing, there are still insufficient human and financial resources for encouraging the growing demand of blood and blood products and new blood donors. Material and Methods: We collected secondary data by using using the order forms of hospitals that used blood and blood products registered in the National Center for Blood Transfusion Research in 2017-2019 in accordance with the retrospective survey method.
In total 34,119 hospital order information sheet was entered into computer in excel program, and converted into SPSS 23 software, descriptive parameters were calculated and analyzed. Results: Compare to the 2017 (n=9076), the demand of blood product was increased by 21.8%, and 54.8% in 2019. There are 51.9% (95%CI: 51.2-52.5) of total users are male, which is statistically significant. The mean age of blood product users were aged 48.58±21.32, the youngest user was aged 1 and the oldest age was 99. The demand of blood products were increased by growing of the age of users. The product usage of age group of 46-55 was 17.8% and has trend to increase year by year. In total, 11.3% of total blood product was utilized for children and 72.3% of them were aged less than 5 years old. 73.0% of total blood products were utilized in specialized hospitals, 14.6 % of them were used in aimag and district level hospitals and 11.3% of them were used in private clinics. 24.4% of blood products utilization was used for diseases of digestive system (К00-К93), 22.1% of them were used for diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism, and 19.5% of them were used for the cancer (C00-C97) disease patient’s treatment. Conclusion Since after new treatment guidance was introduced the blood and blood products usage had been increased.

Background: This paper proposes a novel method for automatically identifying sleep apnea (SA) severity based on deep learning from a short-term normal electrocardiography (ECG) signal. Methods: A convolutional neural network (CNN) was used as an identification model and implemented using a one-dimensional convolutional, pooling, and fully connected layer.An optimal architecture is incorporated into the CNN model for the precise identification of SA severity. A total of 144 subjects were studied. The nocturnal single-lead ECG signal was collected, and the short-term normal ECG was extracted from them. The short-term normal ECG was segmented for a duration of 30 seconds and divided into two datasets for training and evaluation. The training set consists of 82,952 segments (66,360 training set, 16,592 validation set) from 117 subjects, while the test set has 20,738 segments from 27 subjects. Results: F1-score of 98.0% was obtained from the test set. Mild and moderate SA can be identified with an accuracy of 99.0%. Conclusion The results showed the possibility of automatically identifying SA severity based on a short-term normal ECG signal.

BACKGROUND: In this study, we propose a method for automatically predicting atrial fibrillation (AF) based on convolutional neural network (CNN) using a short-term normal electrocardiogram (ECG) signal. METHODS: We designed a CNN model and optimized it by dropout and normalization. One-dimensional convolution, max-pooling, and fully-connected multiple perceptron were used to analyze the short-term normal ECG. The ECG signal was preprocessed and segmented to train and evaluate the proposed CNN model. The training and test sets consisted of the two AF and one normal dataset from the MIT-BIH database. RESULTS: The proposed CNN model for the automatic prediction of AF achieved a high performance with a sensitivity of 98.6%, a specificity of 98.7%, and an accuracy of 98.7%. CONCLUSION: The results show the possibility of automatically predicting AF based on the CNN model using a short-term normal ECG signal. The proposed CNN model for the automatic prediction of AF can be a helpful tool for the early diagnosis of AF in healthcare fields.
Atrial Fibrillation ; Dataset ; Delivery of Health Care ; Early Diagnosis ; Electrocardiography ; Methods ; Neural Networks (Computer) ; Sensitivity and Specificity

Background: Blood is an important resource, both for planned treatments and urgent interventions. It can help patients suffering from life-threatening conditions live longer and with a higher quality of life, and supports complex medical and surgical procedures. According to WHO recommendation at least 1% of the population of any country needs to donate their blood to accommodate the basic clinical needs of the country. Accordingly, we aimed to assess existing attitudes of the general population towards on blood donors. Materials and Methods: The survey identified attitude of the population on blood donation and factors influencing them, using quantitative and qualitative methods. The survey covered a population aged 18-60 years. SPSS software version 21 was used for data analysis of the survey. The survey protocol and methodology were reviewed and approved by the Scientific Committee at the NCPH. The Medical Ethical Committee at the MOH reviewed the survey materials and issued an approval (2015/3). Results: The survey covered in total 3,782 people and there are 59.2% of surveyed respondents said they have never thought of becoming a voluntary blood donor. Positive attitude on blood donation is higher with statistical significance among women (59.0%), 18-25 years old (43.7%) and UB residents citizens with higher education. As education level increases the number of respondents who thought about donating blood is also increases. 16.1% of them had a history of blood donation before and 38.2% said they never thought about it. Twenty point four percent of respondents thought blood donation brings some kind of risk. Nevertheless of the education level of surveyed respondents, the percentage of answer blood donation is not risky for a person was the most common answer. But respondent who is only literal and uneducated were don’t know about whether it has a risk or not (385.37=2א, p=0.000001). Also, respondents failed to donate their blood because the family not allowed, afraid, risk of infection, doesn’t want and had a busy schedule. Conclusion There is a high tendency to donate blood populations of young people aged 20-29, women, residents of Ulaanbaatar, and uneducated and highly educated. The majority of respondents agreed that blood donating is charity and a good deed. The leading causes of blood donation is the education, gender, the desire of doing a good deed, peer influence and health condition.

Thrombosis is a term for a blood clot occurring inside a blood vessel. R. Virchow postulated that abnormalities in blood flow, hypercoagulability of the blood, and injury to the vessel wall are causally related to thrombus formation. Many of the risk factors for deep vein thrombosis aretrauma for 9.3- 18.8%, birth for 16-17.3%, surgery for 14.3-30.3%, infection disease for 9.7-15.9%, cancer for 3.5%, heart disease for 4.6% and 6.9-11.8% of deep vein thrombosis is an indistinct cause. Pain, swelling, warmth, edema and redness in the affected leg are common symptoms.The diagnosis of deep vein thrombosis of the leg can be difficult with clinical findings and history being unreliable. The National Institute of Health and Care Excellence has evidence based recommendations on the prevention and management of a wide range of health conditions. Here: incorporation of a clinical predication score, D-dimer, and venous duplex ultrasound. The D-dimer blood test measures degraded fibrinogen, which is raised in patients with a clot. However, it cannot confirm deep vein thrombosis, as D-dimer can be raised in other conditions including malignancy, infection, pregnancy, post-surgery, inflammation, trauma, disseminated intravascular coagulopathy, and renal impairment. There are two types venous ultrasound as the first line investigation for suspected deep vein thrombosis. The aim of treatment for deep vein thrombosis are:
• The prevention of a thrombus progress
• Decrease the risk of the pulmonary embolism
• The reduction of the thrombus expansion or resolution.
• The prevention of the post thrombotic symptoms
• Decrease the mortality of vein thrombosis
Guidelines from NICE and ACCP recommended direct oral anticoagulants as first line treatment for deep vein thrombosis. Direct oral anticoagulants include direct factor Xa inhibitors apixaban, rivaroxaban, and edoxaban, and a direct thrombin inhibitor dabigatron

In this study, we propose a novel method for obstructive sleep apnea (OSA) detection using a piezo-electric sensor. OSA is a relatively common sleep disorder. However, more than 80% of OSA patients remain undiagnosed. We investigated the feasibility of OSA assessment using a single-channel physiological signal to simplify the OSA screening. We detected both snoring and heartbeat information by using a piezo-electric sensor, and snoring index (SI) and features based on pulse rate variability (PRV) analysis were extracted from the filtered piezo-electric sensor signal. A support vector machine (SVM) was used as a classifier to detect OSA events. The performance of the proposed method was evaluated on 45 patients from mild, moderate, and severe OSA groups. The method achieved a mean sensitivity, specificity, and accuracy of 72.5%, 74.2%, and 71.5%; 85.8%, 80.5%, and 80.0%; and 70.3%, 77.1%, and 71.9% for the mild, moderate, and severe groups, respectively. Finally, these results not only show the feasibility of OSA detection using a piezo-electric sensor, but also illustrate its usefulness for monitoring sleep and diagnosing OSA.
Heart Rate ; Humans ; Mass Screening* ; Methods ; Sensitivity and Specificity ; Sleep Apnea, Obstructive* ; Sleep Wake Disorders ; Snoring ; Support Vector Machine

BACKGROUND. Regular blood donation can lead to pre-clinical iron deficiency as well as iron deficiency anemia. With Each donation donors lose 220-250 mg of iron. Early detection of iron deficiency is important for the blood donors and even useful for blood and blood product safety and supply. The research work we studied present Ret-HE to be used to detect the occurrence of iron deficiency eritrony level. Purpose: The aim of this study was to determine Ret-He to have sensitivity and specificity for diagnosing iron deficiency than traditional iron measurements. Materials and methods: We performed a cross sectional and case control study of 156 blood donors who served National Center for Transfusion Medicine. Ret-He, hemoglobin, plasma iron and ferritin were measured using XN2000 Sysmex, and CobasE600 Roche. The statistical analysis was done using One way Anova, Rock curve, Kruskal Wallis test. Results: We examined 64(41.02%) male donors, 92(58.9%) female donors by measurements of Ret-He,hemoglobin, serum, iron and ferritin. Survey participants were 8.33%(n=13) with anemia, 91.67% (n=143) without anemia. In donors with anemia the results were: RBC 4.9*106 u/l, HGB 10.8 g/dl (10;11), serum ferritin 5.2 (4.3; 6.3) mmol, serum iron 4.5 (3.7; 5.8) mmol and Ret-He 25.5 (22; 26) pg. Donors were divided into 3 age groups: group I age was up to 25years, group II was between 26-35 years, group III age criteria was above 35. Group I had serum iron 13.5 (10.; 18.), serum ferritin 41.8 (14; 78), Ret-He 32.2 (30; 33.) RBC 5×106 u/l (4.6;5), HGB14.2g/dl (13.3;14. 2). Group II had serum iron 14.6 (11; 19), serum ferritin 54.1 μg/l (29; 138), Ret-He 32.2pg (31; 33), RBC 5.1×106 u/l(4.7;5.1), HGB14.8 g/dl (13.5;14.8),Group III had serum iron 15.1 umol/l (9; 20), serum ferritin 95.7 μg/l (39; 141), Ret-He 32.7pg (31; 34) , RBC4.9×106 u/l(4.6;4.9), HGB 14.5g/dl(13.8;14.5), respectively. According to a curve (Roc) analysis, AUC of serum iron was 0.0963, serum ferritin 0.909, Ret-He 0.975. The mean Ret-He was 32.3pg (31.3;33.4). The optimal cut off value for the Ret-He was 29,25pg by ROC analysis and are presented along with sensitivity 92.3% and specificity 95.1%. Conclusion: 1. Determining the amount of Ret-He has a better sensitivity and specificity for diagnosing iron deficiency compared to traditional iron measurements. 2. Ret-He has diagnostic indicators that are able to detect the depletion of iron reserves, erythron level. And it need to be used in further clinical practices, as well as doctors should be required to use it for diagnosis and treatment.