scholarly journals Evaluating the predictive quality of the Chapman bone algorithm using aggregated data sets

2018 ◽  
Vol 6 (1) ◽  
pp. 38
Author(s):  
Noah D. Barrett ◽  
Cameron W. James ◽  
Joshua P. Tam ◽  
Elise S. Levesque ◽  
Anton S. Ketterer ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
Primary Data ◽  
P Value ◽  
Mathematical Treatment ◽  
Data Sets ◽  
Mean Values ◽  
Aggregated Data ◽  
Metabolic Bone Disorder ◽  
Metabolic Bone ◽  
Feasible Alternative

Background: Due to an aging population, osteoporosis has become an increasingly prevalent metabolic bone disorder that is largely undiagnosed worldwide because of inaccessible and expensive DXA machines. The Chapman bone algorithm (CBA), a mathematical treatment that enables osteoporosis determination by using simply-assayed bone metabolites from blood serum, has been previously presented as a cheaper and feasible alternative for analyzing bone health. The CBA has a sensitivity of 1.0 and a specificity of 0.83, with an area under the Receiver Operating Characteristic curve of 0.93. Our goal was to utilize existing data from primary literature sources to determine if the CBA could be applied with similar or equal fidelity.Methods: We obtained mean values from analyses of serum Osteocalcin (s-OC) and serum Pyridinoline (s-PYD) markers in conjunction with patient age from various large-sample data sets available in primary literature.Results: Following analyses of aggregated mean values from the literature, we found that 60% of studies predicted the presence or absence of osteoporosis with the same degree of accuracy between FRAX and CBA methods. Osteoporosis was defined as having a t-score of <-2.5 (FRAX) or surpassing the threshold p-value of >0.035 (CBA).Conclusions: We expected higher agreement between the FRAX scores and our CBA, but this may be due to the aggregated nature of the data. Our findings indicated the need to advance the CBA in analyzing larger-scale primary data sets, underscoring the importance of raw data analysis, to determine the full efficacy of this diagnostic tool.

scholarly journals Deep learning algorithms for detecting and visualising intussusception on plain abdominal radiography in children: a retrospective multicenter study

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Gitaek Kwon ◽  
Jongbin Ryu ◽  
Jaehoon Oh ◽  
Jongwoo Lim ◽  
Bo-kyeong Kang ◽  
...  
Keyword(s):  
Characteristic Curve ◽  
External Validation ◽  
Youden Index ◽  
P Value ◽  
Data Sets ◽  
Single Shot ◽  
X Rays ◽  
Hospital Data ◽  
Data Set ◽  
Mean Values

Abstract This study aimed to verify a deep convolutional neural network (CNN) algorithm to detect intussusception in children using a human-annotated data set of plain abdominal X-rays from affected children. From January 2005 to August 2019, 1449 images were collected from plain abdominal X-rays of patients ≤ 6 years old who were diagnosed with intussusception while 9935 images were collected from patients without intussusception from three tertiary academic hospitals (A, B, and C data sets). Single Shot MultiBox Detector and ResNet were used for abdominal detection and intussusception classification, respectively. The diagnostic performance of the algorithm was analysed using internal and external validation tests. The internal test values after training with two hospital data sets were 0.946 to 0.971 for the area under the receiver operating characteristic curve (AUC), 0.927 to 0.952 for the highest accuracy, and 0.764 to 0.848 for the highest Youden index. The values from external test using the remaining data set were all lower (P-value < 0.001). The mean values of the internal test with all data sets were 0.935 and 0.743 for the AUC and Youden Index, respectively. Detection of intussusception by deep CNN and plain abdominal X-rays could aid in screening for intussusception in children.

The Romanian Constitutional Court's Relationship with the Ordinary Courts: What Are Some of the Causes of Its High Caseload?

2012 ◽  
Vol 37 (1) ◽  
pp. 53-93 ◽  
Author(s):  
Filip Gâdiuţă
Keyword(s):  
Lower Number ◽  
Comparative Perspective ◽  
Primary Data ◽  
Constitutional Court ◽  
Data Sets ◽  
Upward Trend ◽  
Aggregated Data ◽  
Exponential Increase ◽  
Near Future ◽  
Substantial Factor

AbstractThis article examines the recent high caseload of the Romanian Constitutional Court from a comparative perspective. In investigating possible causes of this phenomenon, the author has created several aggregated data sets based on the primary data available on the website of the Romanian Constitutional Court (over 20,000 referrals since 1992) and has examined the following hypotheses, most of which concern relations between the Constitutional Court and the ordinary courts: automatic suspension of proceedings as a delaying tactic, the ordinary courts as a filter, and the possibility of mass litigation as a storm flood caused by the strict ex nunc effects of the decisions of the Constitutional Court. The author has concluded that, while mass litigation is a substantial factor (responsible for three-quarters of the caseload in 2009), there was an underlying upward trend that can be explained by other causes. The available data are not particularly conclusive, but a recent legislative amendment could—in the near future—provide a test of the 'automatic suspension as a delaying tactic' hypothesis. The author also has evaluated the extent to which the Court may have been overwhelmed by the number of cases. Surprisingly, the Court has adjusted rather well to the exponential increase in its caseload since it was established in 1992. While its backlog has increased, the lower number of referrals submitted in 2010 and 2011 should relieve part of the pressure. Furthermore, the author assesses whether key cases involving politicians have been delayed by the Court. The available data seem to indicate that such cases are not being excessively delayed.

User Power Behavior Similarity Clustering Based on Unsupervised Extreme Learning Machine Algorithm

2020 ◽  
Vol 13 (5) ◽  
pp. 641-649
Author(s):  
Yuancheng Li ◽  
Yaqi Cui ◽  
Xiaolong Zhang
Keyword(s):  
Extreme Learning Machine ◽  
Clustering Algorithm ◽  
Characteristic Curve ◽  
Clustering Algorithms ◽  
Data Sets ◽  
Residential Areas ◽  
Processing Power ◽  
Learning Machine ◽  
Advanced Metering ◽  
Matlab Programming

Background: Advanced Metering Infrastructure (AMI) for the smart grid is growing rapidly which results in the exponential growth of data collected and transmitted in the device. By clustering this data, it can give the electricity company a better understanding of the personalized and differentiated needs of the user. Objective: The existing clustering algorithms for processing data generally have some problems, such as insufficient data utilization, high computational complexity and low accuracy of behavior recognition. Methods: In order to improve the clustering accuracy, this paper proposes a new clustering method based on the electrical behavior of the user. Starting with the analysis of user load characteristics, the user electricity data samples were constructed. The daily load characteristic curve was extracted through improved extreme learning machine clustering algorithm and effective index criteria. Moreover, clustering analysis was carried out for different users from industrial areas, commercial areas and residential areas. The improved extreme learning machine algorithm, also called Unsupervised Extreme Learning Machine (US-ELM), is an extension and improvement of the original Extreme Learning Machine (ELM), which realizes the unsupervised clustering task on the basis of the original ELM. Results: Four different data sets have been experimented and compared with other commonly used clustering algorithms by MATLAB programming. The experimental results show that the US-ELM algorithm has higher accuracy in processing power data. Conclusion: The unsupervised ELM algorithm can greatly reduce the time consumption and improve the effectiveness of clustering.

scholarly journals Haemoconcentration as a predictor of severity in acute pancreatitis

2016 ◽  
Vol 4 (1) ◽  
pp. 3-7
Author(s):  
Tanka Prasad Bohara ◽  
Dimindra Karki ◽  
Anuj Parajuli ◽  
Shail Rupakheti ◽  
Mukund Raj Joshi
Keyword(s):  
Acute Pancreatitis ◽  
Pearson Correlation ◽  
Characteristic Curve ◽  
Scoring Systems ◽  
Cost Effective ◽  
Receiver Operator Characteristic Curve ◽  
First Episode ◽  
P Value ◽  
Receiver Operator Characteristic ◽  
Chi Square

Background: Acute pancreatitis is usually a mild and self-limiting disease. About 25 % of patients have severe episode with mortality up to 30%. Early identification of these patients has potential advantages of aggressive treatment at intensive care unit or transfer to higher centre. Several scoring systems are available to predict severity of acute pancreatitis but are cumbersome, take 24 to 48 hours and are dependent on tests that are not universally available. Haematocrit has been used as a predictor of severity of acute pancreatitis but some have doubted its role.Objectives: To study the significance of haematocrit in prediction of severity of acute pancreatitis.Methods: Patients admitted with first episode of acute pancreatitis from February 2014 to July 2014 were included. Haematocrit at admission and 24 hours of admission were compared with severity of acute pancreatitis. Mean, analysis of variance, chi square, pearson correlation and receiver operator characteristic curve were used for statistical analysis.Results: Thirty one patients were included in the study with 16 (51.61%) male and 15 (48.4%) female. Haematocrit at 24 hours of admission was higher in severe acute pancreatitis (P value 0.003). Both haematocrit at admission and at 24 hours had positive correlation with severity of acute pancreatitis (r: 0.387; P value 0.031 and r: 0.584; P value 0.001) respectively.Area under receiver operator characteristic curve for haematocrit at admission and 24 hours were 0.713 (P value 0.175, 95% CI 0.536 - 0.889) and 0.917 (P value 0.008, 95% CI 0.813 – 1.00) respectively.Conclusion: Haematocrit is a simple, cost effective and widely available test and can predict severity of acute pancreatitis.Journal of Kathmandu Medical College, Vol. 4(1) 2015, 3-7

TO COMPARE THE EFFECTIVENESS OF NEBULISATION WITH ADRENALINE, 3% HYPERTONIC SALINE AND NORMAL SALINE IN BRONCHIOLITIS IN CHILDREN OF 2 TO 24 MONTHS OF AGE BASED ON CLINICAL SEVERITY SCORE AND NEBULISATION FREQUENCY.

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Priyanka Jain ◽  
Rakesh Jain
Keyword(s):  
Hypertonic Saline ◽  
Normal Saline ◽  
Mean Difference ◽  
Clinical Severity ◽  
Research Centre ◽  
P Value ◽  
College Hospital ◽  
Mean Values ◽  
Significant Difference ◽  
The Mean

Background & Method: We conducted a double blinded study at Index Medical College Hospital & Research Centre, Indore. The sample size was determined to be minimum of 120 cases as based upon previous years admission due to acute bronchiolitis. Initially, 146 cases were included in the study out of which 23 cases dropped out of the study after giving consent by guardian for participation in the study as they left against medical advice from the hospital. Result: The mean difference of CSS between 0 minutes to 60 minutes of nebulisation between groups in all cases was 0.4 ± 0.6, between 60 minutes and 4 hours was 0.8 ± 0.6, between 4 to 8 hours was 0.7 ± 0.6, between 8-12 hours was 0.6 ± 0.4, between 12-24 hours was 1.6 ± 0.9 and between 24-48 hours was 1.9 ± 0.9.The mean values and resultant p-value of ANOVA of various nebulising agents used for improvement in CSS shows significant association between various nebulising agents used along with improvement in CSS at the end of assessment at 48 hours of treatment. Conclusion: This study was conducted to establish the efficacy of each nebulisation agent (i.e.  adrenaline, 3% hypertonic saline and normal saline) currently used and compare the outcomes as there is not enough evidence amongst Indian population on level of efficacy of each drug in causing improvement in symptoms and signs in various severities of bronchiolitis in early childhood. Comparison of significant improvement in mean difference in CSS at various intervals in all cases compared between groups by post hoc test revealed non-significant difference (p-value 0.700) between 3% hypertonic saline and normal saline. Keywords: nebulisation, adrenaline, bronchiolitis & clinical.

scholarly journals Geriatric Health Charts for Individual Assessment and Prediction of Care Needs: A Population-Based Prospective Study

2018 ◽  
Vol 75 (1) ◽  
pp. 131-138 ◽  
Author(s):  
Giola Santoni ◽  
Amaia Calderón-Larrañaga ◽  
Davide L Vetrano ◽  
Anna-Karin Welmer ◽  
Nicola Orsini ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
P Value ◽  
Care Needs ◽  
Social Care Service ◽  
Health Changes ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Background Geriatric health charts that are similar to pediatric growth charts could facilitate monitoring health changes and predicting care needs in older adults. We aimed to validate an existing composite score (Health Assessment Tool [HAT]) and provide provisional age-specific reference curves for the general older population. Methods Data came from the Swedish National study on Aging and Care in Kungsholmen (N = 3,363 participants aged 60 years and over examined clinically at baseline and 3 years later). HAT was validated by exploring its relationship with health indicators (logistic regression) and comparing its ability to predict care consumption with that of two of its components, morbidity and disability (receiver operating characteristic curve areas). A flowchart was developed to obtain individual-level HAT scores (nominal response method). Sex-specific health charts were derived by graphing seven percentile curves of age-related HAT change (logistic quantile regression). Results HAT scores above the age- and sex-specific median were related to good performance in chair-stand tests (odds ratio [OR] = 2.62, 95% confidence interval [CI]: 2.07–3.31), balance and grip tests (interaction balance grip test, OR = 1.15, 95% CI: 1.05–1.25), and good self-rated health (OR = 2.19, 95% CI: 1.77–2.71). Receiver operating characteristic curve areas (HAT vs number of chronic disorders) were formal care, 0.76 versus 0.58 (p value &lt; .001); informal care, 0.74 versus 0.59 (p value &lt; .001); hospital admission, 0.70 versus 0.66 (p value &lt; .001); primary care visits, 0.71 versus 0.69 (p value &gt; .05); and specialty care visits, 0.62 versus 0.65 (p value &lt; .001). HAT consistently predicted medical and social care service use better than disability. Conclusions HAT is a valid tool that predicts care consumption well and could be useful in developing geriatric health charts to better monitor health changes in older populations.

scholarly journals Tinnitus: The Sound of Stress?

2018 ◽  
Vol 14 (1) ◽  
pp. 264-269 ◽  
Author(s):  
Patricia Ciminelli ◽  
Sergio Machado ◽  
Manoela Palmeira ◽  
Mauro Giovanni Carta ◽  
Sarah Cristina Beirith ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Progressive Increase ◽  
Cross Sectional Study ◽  
P Value ◽  
Cross Sectional ◽  
Mean Values ◽  
Subjective Tinnitus ◽  
Stress Symptoms ◽  
The Impact

Background: Emotional stress is frequently associated with otologic symptoms as tinnitus and dizziness. Stress can contribute to the beginning or worsening of tinnitus. Objective: The objective of the study is to evaluate the presence of stress symptoms in patients with chronic, subjective tinnitus, and correlate its presence to annoyance associated with tinnitus. Methods: This is a cross-sectional study. One hundred and eighty patients with chronic, subjective tinnitus were included. Patients answered the Tinnitus Handicap Inventory (THI) to evaluate the impact of tinnitus in the quality of life and answered the Lipp's inventory symptoms of stress for adults (ISSL). The data obtained was organized using Excel® 2010, mean values, linear regression and p-value were calculated. Results: Of the 180 patients included in the study, 117 (65%) had stress symptoms, 52 of the 117 (44%) were in the resistance phase and 23 of the 117 (20%) in the exhaustion phase, the remaining was in the alert phase. There was a clear progressive increase in stress as THI raised, with more impact of tinnitus in quality of life. Conclusion: The presence of stress symptoms, measured by ISSL was observed in most of our patients with chronic subjective tinnitus, specially in the resistance and exhaustion phases and it is directly associated with tinnitus annoyance.

scholarly journals Influence of the Computer-Aided Decision Support System Design on Ultrasound-Based Breast Cancer Classification

Cancers ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 277
Author(s):  
Zuzanna Anna Magnuska ◽  
Benjamin Theek ◽  
Milita Darguzyte ◽  
Moritz Palmowski ◽  
Elmar Stickeler ◽  
...  
Keyword(s):  
Breast Lesion ◽  
Characteristic Curve ◽  
Cancer Diagnostics ◽  
Lesion Detection ◽  
Machine Learning Algorithms ◽  
Classification Model ◽  
P Value ◽  
Future Design ◽  
Sensitivity Specificity ◽  
Derivatives Of

Automation of medical data analysis is an important topic in modern cancer diagnostics, aiming at robust and reproducible workflows. Therefore, we used a dataset of breast US images (252 malignant and 253 benign cases) to realize and compare different strategies for CAD support in lesion detection and classification. Eight different datasets (including pre-processed and spatially augmented images) were prepared, and machine learning algorithms (i.e., Viola–Jones; YOLOv3) were trained for lesion detection. The radiomics signature (RS) was derived from detection boxes and compared with RS derived from manually obtained segments. Finally, the classification model was established and evaluated concerning accuracy, sensitivity, specificity, and area under the Receiver Operating Characteristic curve. After training on a dataset including logarithmic derivatives of US images, we found that YOLOv3 obtains better results in breast lesion detection (IoU: 0.544 ± 0.081; LE: 0.171 ± 0.009) than the Viola–Jones framework (IoU: 0.399 ± 0.054; LE: 0.096 ± 0.016). Interestingly, our findings show that the classification model trained with RS derived from detection boxes and the model based on the RS derived from a gold standard manual segmentation are comparable (p-value = 0.071). Thus, deriving radiomics signatures from the detection box is a promising technique for building a breast lesion classification model, and may reduce the need for the lesion segmentation step in the future design of CAD systems.

scholarly journals Hubungan Pemberian Anestesi Regional Dengan Kelancaran ASI Pada Ibu Post Partum Sectio Caesarea Di Rumah Sakit Muhammadiyah Gresik

2020 ◽  
Vol 7 (2) ◽  
pp. 42
Author(s):  
Vina Rahmatika ◽  
Musa Ghufron ◽  
Nenny Triastuti ◽  
Syaiful Rochman
Keyword(s):  
Breast Milk ◽  
Caesarean Section ◽  
Post Partum ◽  
Secondary Data ◽  
Sampling Technique ◽  
Primary Data ◽  
Sectio Caesarea ◽  
P Value ◽  
Cross Sectional ◽  
Anesthetic Drugs

Background: The birth rate by caesarean section method is getting higher. Risk data for 2013 shows the method of birth with the operation method of 9.8 percent of the total 49,603 births during 2010 to 2013. Being in practice the mother must be given anesthetic before the surgery begins. This anesthesia will later affect the pain that will occur after SC. Purpose: The purpose of this study was to determine the correlation between regional anesthetic drugs and the smoothness of breast milk in women born in sectio caesarea at Muhammadiyah Gresik Hospital. Method: Method with Cross Sectional approach. The population in this study mothers who gave birth in a caesarean section at Muhammadiyah Hospital Gresik in December 2019 to January 2020. The sampling technique in this study is probability / random simple sampling. The sample in this study was a portion of mothers who gave birth in a caesarean section at Muhammadiyah Gresik Hospital. The instrument used was primary data collection in the form of questionnaires and secondary data in the form of patient medical records. Result: The data obtained in this study were processed using spearman correlation statistics. From the statistical test the Correlation coefficient value was 0.807, and obtained P-Value equal to 0,000 this value is less than 0.05. Conclusion: The conclusion of this study is that there is a correlation between the administration of a regional anesthetics and the smoothness of breast milk in mothers of post partum caesarea at Muhammadiyah Gresik Hospital.

scholarly journals PREVALENCE, INTENSITY AND RISK FACTORS OF SOIL TRANSMITTED HELMINTHS INFECTIONS AMONG ELEMENTARY SCHOOL STUDENTS IN NGIS VILLAGE, KARANGASEM DISTRICT, BALI

2019 ◽  
Vol 7 (6) ◽  
pp. 137
Author(s):  
Sang Ayu Arta Suryantari
Keyword(s):  
Risk Factors ◽  
Elementary School ◽  
Monitoring Program ◽  
Primary Data ◽  
Moderate Intensity ◽  
Single Infection ◽  
P Value ◽  
School Students ◽  
Cross Sectional ◽  
Soil Transmitted Helminths

Soil Transmitted Helminths (STH) infections is one of health issues in Indonesia that has environment and social basis. It is classified as neglected disease. The Indonesian government already has eradication program, but it is not supported by evaluation and monitoring program. The purpose of this study is to determine the prevalence and relation of each risk factors related to STH infections in elementary school in Ngis village, Karangasem regency, Bali. The study was done by analytical description using cross sectional study. Samples were selected from population based on inclusion and exclusion criteria. Primary data about suspected risk factors were collected using questionnaire. Diagnosis was established using Kato-Katz modification method. Data was analyzed using chi-square with confidence interval 95% or p value ≤0.05 categorized as significant. 138 students enrolled in this study, the median age is 9 (6-13) years. The prevalence of STH infections is 10.1% with 78.6% is single infection of Trichuris trichiura and 21.4% mixed infections. The proportion of STH infections in males is higher than female but it is statistically insignificant. STH infections have significant relationship with some risk factors such as not washing hand after defecation, not washing hand after playing with soil, barefoot, not cutting nails and consuming anti-helminthic routinely. The highest risk factor of STH infections in Ngis village is not having available and proper latrine. (OR=33.9; 95%CI=5.749-199.769). The prevalence of STH infection is quite high with mild to moderate intensity and risk factors namely low hygiene and limited latrines. The implementation of monitoring and evaluation can be an effort to control risk factors and stop the STH transmission chain.

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