• Journal of Korean Academy of Nursing
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• v.49 no.5
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• pp.643-654
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• 2019

Purpose: The purpose of this study was to develop and psychometrically test the Korean Geriatric Loneliness Scale (KGLS). Methods: The initial items were based on in-depth interviews with 10 older adults. Psychometric testing was then conducted with 322 community-dwelling older adults aged 65 or older. Content, construct, and criterion-related validity, classification in cutoff point, internal consistency reliability, and test-retest reliability were used for the analysis. Results: Exploratory factor analysis showed three factors, including 15 items explaining 91.6% of the total variance. The three distinct factors were loneliness associated with family relationships (34.3%), social loneliness (32.4%), and a lack of belonging (24.9%). As a result of confirmatory factor analysis, 14 items in the three-factor structure were validated. Receiver operating characteristic analysis demonstrated that the KGLS' cutoff point of 32 was associated with a sensitivity of 71.0%, specificity of 80.2%, and area under the curve of .83. Reliability, as verified by the test-retest intraclass correlation coefficient, was .89, and Cronbach's ${\alpha}$ was .90. Conclusion: As its validity and reliability have been verified through various methods, the KGLS can contribute to assessing loneliness in South Korean older adults.

• Smart Structures and Systems
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• v.29 no.3
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• pp.513-522
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• 2022

Due to the importance of accurate analysis of bearing capacity in civil engineering projects, this paper studies the efficiency of two novel metaheuristic-based models for this objective. To this end, black hole algorithm (BHA) and multi-verse optimizer (MVO) are synthesized with an artificial neural network (ANN) to build the proposed hybrid models. Based on the settlement of a two-layered soil (and a shallow footing) system, the stability values (SV) of 0 and 1 (indicating the stability and failure, respectively) are set as the targets. Each model predicted the SV for 901 stages. The results indicated that the BHA and MVO can increase the accuracy (i.e., the area under the receiving operating characteristic curve) of the ANN from 94.0% to 96.3 and 97.2% in analyzing the SV pattern. Moreover, the prediction accuracy rose from 93.1% to 94.4 and 95.0%. Also, a comparison between the ANN's error decreased by the BHA and MVO (7.92% vs. 18.08% in the training phase and 6.28% vs. 13.62% in the testing phase) showed that the MVO is a more efficient optimizer. Hence, the suggested MVO-ANN can be used as a reliable approach for the practical estimation of bearing capacity.

• Asia-Pacific Journal of Business
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• v.13 no.2
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• pp.107-122
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• 2022

Purpose - This study aims to develop machine learning models to predict administrative issue designation in KOSDAQ Market using financial data. Design/methodology/approach - Employing four classification techniques including logistic regression, support vector machine, random forest, and gradient boosting to a matched sample of five hundred and thirty-six firms over an eight-year period, the authors develop prediction models and explore the practicality of the models. Findings - The resulting four binary selection models reveal overall satisfactory classification performance in terms of various measures including AUC (area under the receiver operating characteristic curve), accuracy, F1-score, and top quartile lift, while the ensemble models (random forest and gradienct boosting) outperform the others in terms of most measures. Research implications or Originality - Although the assessment of administrative issue potential of firms is critical information to investors and financial institutions, detailed empirical investigation has lagged behind. The current research fills this gap in the literature by proposing parsimonious prediction models based on a few financial variables and validating the applicability of the models.

• Journal of Trauma and Injury
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• v.35 no.4
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• pp.268-276
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• 2022

Purpose: Rib fractures are common injuries that can lead to morbidity and mortality. Methods: Data on all patients with rib fractures admitted to a single trauma center between January 1, 2008 and December 31, 2018 were reviewed. Results: A total of 1,671 admissions for rib fracture were examined. Patients' median age was 57 years, the median Injury Severity Score (ISS) was 14, and the median number of fractured ribs was three. The in-hospital mortality rate was 4%. Age, the number of rib fractures, and Charlson Comorbidity Index scores were poor predictors of mortality, while the ISS was a slightly better predictor, with area under the receiver operating characteristic curve values of 0.60, 0.55, 0.58, and 0.74, respectively. Multivariate regression showed that age, ISS, and Charlson Comorbidity Index score, but not the number of rib fractures, were associated with significantly elevated adjusted odds ratios for mortality (1.03, 1.14, and 1.28, respectively). Conclusions: Age, ISS, and comorbidities were independently associated with the risk of mortality; however, they were not accurate predictors of death. The factors associated with rib fracture mortality are complex and cannot be explained by a single variable. Interventions to improve outcomes must be multifaceted.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.49 no.3
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• pp.135-141
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• 2023

Objectives: This study aimed to develop and validate machine learning (ML) models using H₂O-AutoML, an automated ML program, for predicting medication-related osteonecrosis of the jaw (MRONJ) in patients with osteoporosis undergoing tooth extraction or implantation. Patients and Methods: We conducted a retrospective chart review of 340 patients who visited Dankook University Dental Hospital between January 2019 and June 2022 who met the following inclusion criteria: female, age ≥55 years, osteoporosis treated with antiresorptive therapy, and recent dental extraction or implantation. We considered medication administration and duration, demographics, and systemic factors (age and medical history). Local factors, such as surgical method, number of operated teeth, and operation area, were also included. Six algorithms were used to generate the MRONJ prediction model. Results: Gradient boosting demonstrated the best diagnostic accuracy, with an area under the receiver operating characteristic curve (AUC) of 0.8283. Validation with the test dataset yielded a stable AUC of 0.7526. Variable importance analysis identified duration of medication as the most important variable, followed by age, number of teeth operated, and operation site. Conclusion: ML models can help predict MRONJ occurrence in patients with osteoporosis undergoing tooth extraction or implantation based on questionnaire data acquired at the first visit.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1697-1707
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• 2021

The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness of the recent modeling approaches and unfamiliarity with the model outputs may confuse some researchers and practitioners about the evaluation of the performance of such models. Methodological literacy to critically appraise the performance evaluation of the models and, ideally, the ability to conduct such an evaluation would be needed for those who want to develop models or apply them in practice. This article intends to provide intuitive, conceptual, and practical explanations of the statistical methods for evaluating the performance of survival prediction models with minimal usage of mathematical descriptions. It covers from conventional to deep learning methods, and emphasis has been placed on recent modeling approaches. This review article includes straightforward explanations of C indices (Harrell's C index, etc.), time-dependent receiver operating characteristic curve analysis, calibration plot, other methods for evaluating the calibration performance, and Brier score.

• Hip & pelvis
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• v.35 no.3
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• pp.164-174
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• 2023

Purpose: This study investigates the relationship between preoperative neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-C-reactive protein ratio (LCR), albumin, and 2-year mortality in elderly patients having hemiarthroplasty for displaced femoral neck fracture (FNF). Materials and Methods: We retrospectively reviewed 284 elderly patients who underwent hemiarthroplasty for Garden type IV FNF from September 2014 to September 2020. Using the receiver operating characteristic curve, optimal cutoff values for LCR, NLR, and albumin were established, and patients were categorized as low or high. Associations with 2-year mortality were evaluated through univariate and multivariate Cox regression analyses. Results: Of the 284 patients, 124 patients (45.9%) died within 2 years post-surgery. The optimal cutoff values were: LCR at 7.758 (specificity 58.5%, sensitivity 25.0%), NLR at 3.854 (specificity 39.2%, sensitivity 40.0%), and albumin at 3.750 (specificity 65.9%, sensitivity 21.9%). Patients with low LCR (<7.758), high NLR (≥3.854), and low albumin (<3.750) had a statistically significant reduced survival time compared to their counterparts. Conclusion: Lower preoperative LCR and albumin levels, along with higher NLR, effectively predict 2-year mortality and 30-day post-surgery complications in elderly patients with Garden type IV FNF undergoing hemiarthroplasty.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.2
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• pp.88-94
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• 2024

Purpose: Infantile hypertrophic pyloric stenosis (IHPS) is a common gastrointestinal disease in neonates and hypochloremia metabolic alkalosis is a typical laboratory finding in affected patients. This study aimed to analyze the clinical characteristics of infants with IHPS and evaluate the association of clinical and laboratory parameters with ultrasonographic findings. Methods: Infants diagnosed with IHPS between January 2017 and July 2022 were retrospectively evaluated. Results: A total of 67 patients were included in the study. The mean age at diagnosis was 40.5±19.59 days, and the mean symptom duration was 11.97±9.91 days. The mean pyloric muscle thickness and pyloric canal length were 4.87±1.05 mm and 19.6±3.46 mm, respectively. Hyponatremia and metabolic alkalosis were observed in five (7.5%) and 36 (53.7%) patients, respectively. Serum sodium (p=0.011), potassium (p=0.023), and chloride levels (p=0.015) were significantly lower in patients with high bicarbonate levels (≥30 mmol/L). Furthermore, pyloric canal length was significantly higher in patients with high bicarbonate levels (p=0.015). To assess metabolic alkalosis in IHPS patients, the area under the receiver operating characteristic curve of pyloric canal length was 0.910 and the optimal cutoff value of the pyloric canal length was 23.5 mm. Conclusion: We found a close association between laboratory and ultrasonographic findings of IHPS. Clinicians should give special consideration to patients with pyloric lengths exceeding 23.5 mm and appropriate fluid rehydration should be given to these patients.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.11-23
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• 2024

Triage is a practice of accurately prioritizing patients in emergency department (ED) based on their medical condition to provide them with proper treatment service. The variation in triage assessment among medical staff can cause mis-triage which affect the patients negatively. Developing ED triage system based on machine learning (ML) techniques can lead to accurate and efficient triage outcomes. This study aspires to develop a triage system using machine learning techniques to predict ED triage levels using patients' information. We conducted a retrospective study using Security Forces Hospital ED data, from 2021 through 2023 during Hajj period in Saudia Arabi. Using demographics, vital signs, and chief complaints as predictors, two machine learning models were investigated, naming gradient boosted decision tree (XGB) and deep neural network (DNN). The models were trained to predict ED triage levels and their predictive performance was evaluated using area under the receiver operating characteristic curve (AUC) and confusion matrix. A total of 11,584 ED visits were collected and used in this study. XGB and DNN models exhibit high abilities in the predicting performance with AUC-ROC scores 0.85 and 0.82, respectively. Compared to the traditional approach, our proposed system demonstrated better performance and can be implemented in real-world clinical settings. Utilizing ML applications can power the triage decision-making, clinical care, and resource utilization.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.24-30
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• 2009

Purpose: Today, Prostate cancer has been gradually increasing, according to the change of internal incidence rate of cancer. Generally, prostate cancer has lead to dead over 90%, in case of metastasis of lymph node and bone. So, innovative development of new radiopharmaceutical and imaging modality is progressed for detection of that metastasis, in nuclear medicine, now. Therefore, this study shows the usefulness of $^{18}F$-Fluoride PET/CT improved diagnosability on bone metastasis of prostate cancer. Materials and Methods: In this study, 33 male patients with prostate cancer were examined (The mean age: $67.8{\pm}10.2$ years old). Every patient was done each whole body bone scan (WBBS) and $^{18}F$-Fluoride positron emission tomography/computed tomography ($^{18}F$-Fluoride PET/CT). And then, using Receiver Operating Characteristic Curve (ROC curve), each sensitivity and specificity of two modalities was measured and compared with. Results: In 22 patients (66.6%) of all, bone metastasis was detected. And, in WBBS, sensitivity was 63.6%, specificity, 81.8%; in $^{18}F$-Fluoride PET/CT, sensitivity was 100% and specificity was 90.9%. As a result of ROC curve, AUROC (The Area under an ROC) of WBBS was 0.778, and that of $^{18}F$-Fluoride PET/CT, 0.942. Conclusions: $^{18}F$-Fluoride PET/CT was higher both sensitivity and specificity than WBBS, and it was valuable to detect bone metastasis of prostate cancer more definitely, with 3D imaging realization. Also, in $^{18}F$-Fluoride PET/CT, physiological images were acquired in more short time than WBBS, so, it was possible to reduce patient's waiting time and complaint. Therefore, it is considered that $^{18}F$-Fluoride PET/CT is able to improve diagnosability by offering more accurate images, as cuts in a share of high cost.