Technology and Health Care - Volume Pre-press, issue Pre-press
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Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: BACKGROUND: Periodontitis (PD), a form of gum disease, is a major public health concern as it is globally prevalent and harms both individual quality of life and economic productivity. Global cost in lost productivity is estimated at US$54 billion annually. Moreover, current PD assessment applies only after the damage has already occurred. OBJECTIVE: This study proposes and tests a new PD risk assessment model applicable at point-of-care, using supervised machine learning methods. METHODS: We compare the performance of five algorithms using retrospective clinical data: Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine…(SVM), Artificial Neural Network (ANN), and Decision Tree (DT). RESULTS: DT and ANN demonstrated higher accuracy in classifying the patients with high or low PD risk as compared to NB, LR and SVM. The resultant model with DT showed a sensitivity of 87.08% (95% CI 84.12% to 89.76%) and specificity of 93.5% (95% CI 91% to 95.49%). CONCLUSIONS: A predictive model with high sensitivity and specificity to stratify individuals into low and high PD risk tiers was developed. Validation in other populations will inform translational value of this approach and its potential applicability as clinical decision support tool.
Keywords: Data mining, decision support systems clinical, health information systems, smoking, electronic health records, information storage and retrieval
Abstract: BACKGROUND: An electroencephalogram (EEG) is the most dominant method for detecting epileptic seizures. However, the existing techniques use single-channel EEGs from public databases and the sample size is small. OBJECTIVE: This study proposes a strategy to distinguish multichannel EEGs for health control, particularly the interictal and ictal multichannel EEGs of epileptic patients. METHOD: We calculated five features (variance, Pearson correlation coefficient, Hoeffding’s D measure, Shannon entropy, inter-quartile range), which are based on maximal overlap discrete wavelet transform. These features were then fed into linear discriminant analysis for classification purposes. Finally, the proposed method…was tested on data on 34 healthy people, 21 interictal patients and 30 ictal patients taken from a hospital. RESULTS: Our experimental results show that the accuracy between healthy and epileptic seizures was 96.88% and the area under the curve (AUC) is 1. The accuracy between interictal and epileptic seizures was 94.12% and the AUC was 0.97. We also obtained an accuracy and AUC equal to 1 for discrimination of interictal EEGs from normal. Finally, we obtained an AUC of 0.83 and an accuracy of 85.88% for discrimination in these three classes. Therefore, our study achieves sufficient performance. CONCLUSIONS: Our proposed method can serve as an auxiliary tool for clinicians who wish to make clinical decisions and reduces the burden of detecting epileptic seizures.
Abstract: BACKGROUND: The Plantago asiatica L. is easy to cultivate and has been used as a folk remedy since ancient times because of various pharmacological actions such as anti-inflammation and antioxidation. It also contains a variety of flavonoids such as aucubin, which is thought to be excellent for whitening, antioxidant and anti-inflammatory action. OBJECTIVE: We investigated the effect of P. asiatica L. leaf ethanol extracts containing various active ingredients on antioxidative, anti-inflammation and whitening action and investigated its potential as a health care material. P. asiatica L. has been widely used in folk remedies.…RESULTS: The cell toxicity test using RAW264.7 cells showed a high cell survival rate of over 75%, thus demonstrating the safety of the sample. In order to study the antioxidant activity of P. asiatica L. leaf ethanol extracts, we studied a sample which showed radical scavenging activity in a dose-dependent manner. To observe the antioxidant activity at the cell level, RAW 264.7 cells were used and inhibition of ROS production was measured. The ROS production was suppressed in a dose-dependent manner and the scavenging activity was stronger than the sample’s own radical scavenging ability. To observe the anti-inflammatory effect of P. asiatica L. leaf ethanol extracts, inhibition of NO generation was observed using LPS-induced RAW 264.7 cells. NO generation was inhibited in a dose-dependent manner and was strongly inhibited by 31% at 100 μ g/mL. In vitro , L-DOPA and L-tyrosine were used to inhibit tyrosinase action in a dose-dependent manner. The concentration of melanin at 1, 10, and 100 μ g/mL was suppressed in B16 F10 melanin cells supplemented with α -MSH in the cells, and the inhibition was suppressed to 29% at 100 μ g/mL. In the B16 F10 melanin cell stimulated with MSH, the P. asiatica L. leaf ethanol extracts inhibited melanin formation in a dose-dependent manner. CONCLUSION: P. asiatica L. leaf ethanol extracts are expected to be developed as whitening cosmeceutical ingredients and as health care ingredients with antioxidant and anti-inflammatory properties.
Abstract: BACKGROUND: This study was planned to investigate the research trends related to naturally derived anti-inflammatory and anti-obesity components. The main purpose of this study was to find out and develop natural health cosmetic ingredients which has high effects on lipid degradation, moisturizing and elasticity enhancement. OBJECTIVE: We all hope this research provided systematic and practical data that can suggest an opportunity to further develop new products. METHODS: This is a descriptive research which classified the natural and traditional components that have important obesity management effects based on the experimental technique (in vitro…and in vivo ). we investigated the effects of 13 natural raw materials selected through preliminary investigation on lipid metabolism related enzyme activity. We first introduced Ainsliaea acerifolea, Onion, pear, Sanguisorba, Limonium tetragonum, Cornus walteri, Loquat, and Loquat-which have recently been shown to be effective in anti-obesity tests, and then described the research methods by showing the effects of onion extracts, Glasswort, Pine Cone (Korean white pine), Orostachys japonicus, African mangoes, Pepper, and Clathratum (sea weed), which actually had effects on anti-obesity in the in vivo experiment. RESULTS: As a result of investigating the effect of 13 natural raw materials selected through a preliminary investigation on lipid metabolism related enzyme activity, the study found nature-derived ingredients which induce anti-inflammatory and enhance the anti-obesity enzyme activity, and ingredients showing myriads of biological activities such as anti-oxidant, body fat reduction, lowering of blood cholesterol, and weight control. CONCLUSION: In this paper, we would like to delve into the possibility of using natural components with natural lipid-lowering effect, and systematically and practically study if they can actually be helpful to develop new cosmetic products.
Abstract: BACKGROUND: Drug-eluting stent technology has rapidly developed in recent years. In particular, stents are used in percutaneous coronary intervention (PCI), which has become a vital method in clinic treatment. Although various methods are currently used to prepare drug-eluting stents, these methods are associated with respective limitations. OBJECTIVE: To design equipment for preparing drug-eluting stents with single-sided coating and to precisely accomplish the drug-coating process for a single side. METHODS: This coating equipment prepared stents in three stages: the precise displacement and translational motion and rotational motion of the operating platform; the recognition and…positioning of the stent strut; and the utilisation of a pL-scale inkjet system. In order to control and synchronise the work of each subsystem, a central processing unit was installed. RESULTS: Through the analysis and solutions of various problems occurring in the experiment, the spraying equipment was improved, and its functions were perfected. Thus, the successful operation of the spraying equipment was realised. CONCLUSIONS: The design of the equipment introduced in this article meets the requirements for preparing drug-eluting stents.
Keywords: Coating equipment design, drug-eluting stent, single-sided drug coating
Abstract: BACKGROUND: The development of antibacterial materials using various traditional food ingredients will be valuable to inhibit Helicobacter pylori in the future. The vegetables and herbs used in this study were food ingredients that normal people eat every day. This paper can be used as a resource for healthcare. OBJECTIVE: This paper presents the design to investigate the antibacterial effect of 20 vegetables and herbs used as traditional food ingredients on H. pylori . METHODS: The antibacterial effect on H. pylori was studied using the disk diffusion test on the activity of…H. pylori . For the control group, 50 mg/ml of Metronidazol, a widely used antibiotic, was used. In particular, four herbs of Artemisia argyi, Scutellaria baicalensis, Annona muricata and Agrimonia pilosa were selected to measure the microbial viability assay, MTT assay, and antioxidant activity owing to the DPPH free radical elimination ability. RESULTS: The measurement results showed that Annona muricata and Agrimonia pilosa had an antibacterial effect on H. pylori and all four herbs were safe in terms of cytotoxicity. The measurement results on the antioxidant activity showed that Scutellaria baicalensia was the best. Annona muricata and Agrimonia pilosa also had an antioxidant activity. CONCLUSIONS: The study results on antibacterial effect of traditional food ingredients of vegetables and herbs on H. pylori showed that Scutellaria baicalensis, Annona muricata and Agrimonia pilosa can be considered as healthcare functional materials through the inhibition of H. Pylori .
Abstract: BACKGROUND: Efficient resource management should consider the improvement of internal factors first as the unique task of medical institutions that can perform the medical services for efficient hospital management under the optimum management condition. OBJECTIVE: This study aims to suggest the efficient model for nurse resource management that can estimate optimum nurse resources according to the nursing intensity of the hospitalized patients. METHODS: The study was performed with four steps including collection and analysis of requirements, system design, system realization, and evaluation, which took 2 years and 10 months. The measurement tool used…in the step of system evaluation was a modified version of Questionnaire for User Interaction Satisfaction (QUIS) 5.0. RESULTS: The system was implemented using Oracle database with Power Builder by Sybase. NRS, PCS, and ONMES were realized with developed NRMIS, and the survey was conducted on the usefulness as the system evaluation. The system evaluation results of User Interaction Satisfaction, means scores of ONMES, PCS, and NRS were 7.15 ± 0.52, 6.21 ± 1.11, and 6.03 ± 1.14 out of 9 points, respectively. Demonstrating the positive change in the subjective usefulness of the respondents after using the system compared to the period before using the system (F = 16.551, p = 0.000). CONCLUSION: It was confirmed that this system contributed to an enhancement of the working process speed, efficiency, and accuracy by simplifying the works which were the purposes of the nursing information system, which changes dynamically, to support decision making on the management of effective and flexible nurse resources.
Keywords: Healthcare personnel staffing and scheduling, hospital information system, nursing intensity, User Interaction satisfaction, patients/classification
Abstract: BACKGROUND: Supporting the caregivers of dementia patients is an important issue in the field of public health. OBJECTIVE: This study established a model for predicting the depression of dementia caregivers while considering the sociodemographic and health science characteristics of South Koreans. The results of this study provided baseline data for developing and applying a caregiver management App. METHODS: This study analyzed 2,592 adults (⩾ 19 years old; 1154 men and 1438 women) who were caregivers (e.g., family and caregivers) of demented elderly (⩾ 60 years old).…RESULTS: The results of developed random forest model showed that gender, subjective health status, disease or accidence experience within the past two weeks, the frequency of meeting a relative, economic activity, and monthly mean household income were the major predictors for the depression of caregivers. The prediction accuracy of the model was better than K-NN and support vector machine. CONCLUSIONS: It was proved that the developed random forest-based App for predicting and managing the depression of dementia caregivers used an algorithm that has a high predictive power. It is required to develop a customized home care system that can prevent and manage the depression of the caregiver.
Keywords: Random forest, healthcare, Alzheimer’s Disease, depression
Abstract: BACKGROUND: The changes in dietary habits can affect mental health problems, such as depressive disorder, due to the occurrence of diabetes. OBJECTIVE: This study aimed to determine the effects of diabetes on mental health (Patient Health Questionnaire-9: PHQ-9). METHODS: A secondary data analysis of cross-sectional design based on the raw data from KNHANES VII-1 was performed, which were disclosed by MOHW and KCDC. Of 8,150 respondents, 5,661 respondents aged ⩾ 20 years were included, thus excluding 2,489 respondents. Data were analyzed using an SPSS version 20.0 program. RESULTS:…The respondents scored high for diabetes diagnosis status (3.65), suicide planning status for a year (8.56), mental problem counseling for a year (7.80), and the degree of daily stress awareness (8.27) in PHQ-9. They scored higher for suicide planning status for a year, mental problem counseling for a year, and the degree of daily stress awareness than for diabetes diagnosis status in PHQ-9. Positive correlation was found among diabetes diagnosis status, suicide planning status for a year, mental problem counseling for a year, and daily stress awareness in PHQ-9 (p < 0.01). Diabetes diagnosis status (p < 0.01), suicide planning status for a year (p < 0.001), mental problem counseling for a year (p < 0.001), and the degree of daily stress awareness (p < 0.001) affected PHQ-9. CONCLUSION: PHQ-9 for screening depressive disorder based on diabetes diagnosis status had low scoring distribution. However, because diabetes diagnosis status significantly affected PHQ-9 for depression screening, it is necessary to pay attention to health care related to diabetes. Further research should be conducted on the association with diverse causes of the low scoring distribution in PHQ-9 in relation to diabetes.
Keywords: Diabetes, mental health, PHQ-9, stress, mental problem counseling
Abstract: BACKGROUND: Applied research on artificial intelligence, mainly in deep learning, is widely performed. If medical images can be evaluated using artificial intelligence, this could substantially improve examination efficiency. OBJECTIVE: We investigated an evaluation system for medical images with different noise characteristics using a deep convolutional neural network. METHODS: Simulated computed tomography images are the targets of the system. We used an AlexNet trained with natural images for the deep convolutional neural network and a support vector machine for classification. Synthetic computed tomography images with circular and rectangular signal bodies at different levels of…contrast and added Gaussian noise were used for training and testing. RESULTS: Two transfer learning methods were tested: classification by a re-trained support vector machine using the AlexNet features, and a method that fine-tuned the deep convolutional neural network. Using the first method, all the test image noise levels could be classified correctly. The fine-tuning method achieved an accuracy rate of 92.6%. CONCLUSIONS: An image quality evaluation method using artificial intelligence will be useful for clinical images and different image quality indices in the future.