scholarly journals Is ultrasonography useful for population studies on schistosomiasis mansoni? An evaluation based on a survey on a population from Kome Island, Tanzania

2016 ◽  
Vol 5 (12) ◽  
pp. 205846011668639 ◽  
Author(s):  
Mats SL Asztely ◽  
Bo Eriksson ◽  
Reverianus M Gabone ◽  
Lars-Åke Nilsson
Keyword(s):  
Population Studies ◽  
Lake Victoria ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Disease Stage ◽  
Population Surveys ◽  
K Value ◽  
Schistosomiasis Mansoni ◽  
Liver Ultrasonography

Background Observation of characteristic alterations at liver ultrasonography in clinical schistosomiasis mansoni cases has initiated utilization of this examination method in population surveys in areas where this disease is endemic. Purpose To present results of liver ultrasonography and their relation to epidemiological data of a population in an area endemic for S. mansoni, to estimate the precision of classification of periportal anatomy changes known as periportal fibrosis (PPF), and to evaluate the relevance of ultrasonography in epidemiological studies on S. mansoni. Material and Methods A total of 459 inhabitants on Kome Island, Lake Victoria, Tanzania were examined by ultrasound with image documentation by locally trained personnel. A subsample of this population, 116 individuals, was subject to ultrasonography by two examiners independently. Separately, the images were classified for PPF according to the Managil protocol, twice for the subsample. Results PPF could be classified for 458 individuals; 64% and 36% were classified as I or II, respectively; none was classified as 0; only one as III. Results were similar for the subsample examined twice. Comparing the two separate classifications of all 232 sets of images of the subsample gave a Kappa (K) value of 0.50. When comparing the classifications of each of the two different examinations of the same individuals of the subsample, K values of 0.29 and 0.34 for the first and second classification, respectively, were obtained. Conclusion Ultrasonography does not appear to correlate well with disease stage. Presently, it should not be utilized for staging of schistosoma mansoni-related liver damage in population surveys.

A Study on Nuclei Shape Features at the Classification of Glioma Disease Stage Using CNN

2020 ◽  
Vol 140 (12) ◽  
pp. 1367-1368
Author(s):  
Daisuke Saito ◽  
Hiroharu Kawanaka ◽  
V. B. Surya Prasath ◽  
Bruce J. Aronow
Keyword(s):  
Disease Stage ◽  
Shape Features

Optimization of K Value in KNN Algorithm for Spam and Ham Email Classification

2020 ◽  
Vol 4 (2) ◽  
pp. 377-383
Author(s):  
Eko Laksono ◽  
Achmad Basuki ◽  
Fitra Bachtiar
Keyword(s):  
Frequency Distribution ◽  
Confusion Matrix ◽  
High Accuracy ◽  
K Value ◽  
A Value ◽  
Optimal Value ◽  
Classification Evaluation ◽  
Email Spam ◽  
Email Classification

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.

Depression, pain, and site:

1999 ◽  
Vol 15 (1) ◽  
pp. 10-17
Author(s):  
Molina Omar Franklin ◽  
Tavares Gimenes Pablo ◽  
Aquilino Raphael ◽  
Rank Rise ◽  
Coelho Santos Zeila ◽  
...  
Keyword(s):  
Visual Analogue Scale ◽  
Beck Depression Inventory ◽  
Temporomandibular Disorders ◽  
Analogue Scale ◽  
Epidemiological Data ◽  
Depression Severity ◽  
Internal Joint ◽  
The Difference ◽  
Biomechanical Tests

Objective: To assess the level of depression, severity of pain and pain in single/multiple sites in patients with different severity of bruxing behavior and Temporomandibular Disorders (TMDs). Methods: We evaluated 131 patients with bruxism and TMDs: 20 patients with mild bruxism, 42 patients with moderate bruxism, 45 patients with severe bruxism and 24 patients with extreme bruxism. We used the Beck Depression Inventory (BDI), clinical examination, a questionnaire of clinical epidemiological data, criteria for TMDs and bruxism, palpation of muscles and joints, the Visual Analogue Scale for pain, classification of the occlusion and biomechanical tests to assess for internal joint derangements. Results: The level of depression increased from the mild, to the moderate, severe and extreme bruxing behavior groups, but the difference was significant only from the mild to the extreme group (p<0.001). Pain levels increased from the mild and moderate to the severe and extreme subgroups, but were not statistically significant. Mean number of pain sites increased from the mild, to the moderate, severe and extreme subgroup and the difference was extremely significant (p<0.0001). Conclusion: Levels of depression, severity of pain and pain sites increased with severity of bruxing behavior. A higher number of pain sites with more severe bruxism indicates somatization in bruxers, but a further study using the same protocol and a psychological test for somatization would be indicated to further substantiate these findings.

Multiclass machine learning classification of functional brain images for Parkinson's disease stage prediction

2020 ◽  
Vol 13 (5) ◽  
pp. 508-523 ◽  
Author(s):  
Guan‐Hua Huang ◽  
Chih‐Hsuan Lin ◽  
Yu‐Ren Cai ◽  
Tai‐Been Chen ◽  
Shih‐Yen Hsu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Disease Stage ◽  
Brain Images ◽  
Functional Brain ◽  
Machine Learning Classification

scholarly journals Methods for epidemiological studies in competitive cycling: an extension of the IOC consensus statement on methods for recording and reporting of epidemiological data on injury and illness in sport 2020

2021 ◽  
pp. bjsports-2020-103906
Author(s):  
Benjamin Clarsen ◽  
Babette M Pluim ◽  
Víctor Moreno-Pérez ◽  
Xavier Bigard ◽  
Cheri Blauwet ◽  
...  
Keyword(s):  
Consensus Statement ◽  
Expert Panel ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Population Characteristics ◽  
Exposure Study ◽  
Injury Mechanisms ◽  
Study Population ◽  
Final Manuscript ◽  
Collection Methods

In 2020, the IOC released a consensus statement that provides overall guidelines for the recording and reporting of epidemiological data on injury and illness in sport. Some aspects of this statement need to be further specified on a sport-by-sport basis. To extend the IOC consensus statement on methods for recording and reporting of epidemiological data on injury and illness in sports and to meet the sport-specific requirements of all cycling disciplines regulated by the Union Cycliste Internationale (UCI). A panel of 20 experts, all with experience in cycling or cycling medicine, participated in the drafting of this cycling-specific extension of the IOC consensus statement. In preparation, panel members were sent the IOC consensus statement, the first draft of this manuscript and a list of topics to be discussed. The expert panel met in July 2020 for a 1-day video conference to discuss the manuscript and specific topics. The final manuscript was developed in an iterative process involving all panel members. This paper extends the IOC consensus statement to provide cycling-specific recommendations on health problem definitions, mode of onset, injury mechanisms and circumstances, diagnosis classifications, exposure, study population characteristics and data collection methods. Recommendations apply to all UCI cycling disciplines, for both able-bodied cyclists and para-cyclists. The recommendations presented in this consensus statement will improve the consistency and accuracy of future epidemiological studies of injury and illness in cycling.

scholarly journals Genetic Contribution of Endometriosis to the Risk of Developing Hormone-Related Cancers

2021 ◽  
Vol 22 (11) ◽  
pp. 6083
Author(s):  
Aintzane Rueda-Martínez ◽  
Aiara Garitazelaia ◽  
Ariadna Cilleros-Portet ◽  
Sergi Marí ◽  
Rebeca Arauzo ◽  
...  
Keyword(s):  
Mendelian Randomization ◽  
Clear Cell ◽  
Association Studies ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genomic Analyses ◽  
Gynecological Disorder ◽  
Robust Evidence

Endometriosis is a common gynecological disorder that has been associated with endometrial, breast and epithelial ovarian cancers in epidemiological studies. Since complex diseases are a result of multiple environmental and genetic factors, we hypothesized that the biological mechanism underlying their comorbidity might be explained, at least in part, by shared genetics. To assess their potential genetic relationship, we performed a two-sample mendelian randomization (2SMR) analysis on results from public genome-wide association studies (GWAS). This analysis confirmed previously reported genetic pleiotropy between endometriosis and endometrial cancer. We present robust evidence supporting a causal genetic association between endometriosis and ovarian cancer, particularly with the clear cell and endometrioid subtypes. Our study also identified genetic variants that could explain those associations, opening the door to further functional experiments. Overall, this work demonstrates the value of genomic analyses to support epidemiological data, and to identify targets of relevance in multiple disorders.

scholarly journals Measles Virus IgG Avidity Assay for Use in Classification of Measles Vaccine Failure in Measles Elimination Settings

2012 ◽  
Vol 19 (11) ◽  
pp. 1810-1817 ◽  
Author(s):  
Sara Mercader ◽  
Philip Garcia ◽  
William J. Bellini
Keyword(s):  
Measles Virus ◽  
Area Under The Curve ◽  
Epidemiological Data ◽  
Diagnostic Tools ◽  
High Avidity ◽  
Characteristic Analysis ◽  
Vaccine Failure ◽  
Avidity Assay ◽  
Igg Avidity

ABSTRACTIn regions where endemic measles virus has been eliminated, diagnostic assays are needed to assist in correctly classifying measles cases irrespective of vaccination status. A measles IgG avidity assay was configured using a commercially available measles-specific IgG enzyme immunoassay by modifying the protocol to include three 5-min washes with diethylamine (60 mM; pH 10.25) following serum incubation; serum was serially diluted, and the results were expressed as the end titer avidity index. Receiver operating characteristic analysis was used for evaluation and validation and to establish low (≤30%) and high (≥70%) end titer avidity thresholds. Analysis of 319 serum specimens expected to contain either high- or low-avidity antibodies according to clinical and epidemiological data indicated that the assay is highly accurate, with an area under the curve of 0.998 (95% confidence interval [CI], 0.978 to 1.000), sensitivity of 91.9% (95% CI, 83.2% to 97.0%), and specificity of 98.4% (95% CI, 91.6% to 100%). The assay is rapid (<2 h) and precise (standard deviation [SD], 4% to 7%). In 18 samples from an elimination setting outbreak, the assay identified 2 acute measles cases with low-avidity results; both were IgM-positive samples. Additionally, 11 patients (15 samples) with modified measles who were found to have high-avidity IgG results were classified as secondary vaccine failures; one sample with an intermediate-avidity result was not interpretable. In elimination settings, measles IgG avidity assays can complement existing diagnostic tools in confirming unvaccinated acute cases and, in conjunction with adequate clinical and epidemiologic investigation, aid in the classification of vaccine failure cases.

scholarly journals A deep cascaded segmentation of obstructive sleep apnea-relevant organs from sagittal spine MRI

2021 ◽  
Vol 16 (4) ◽  
pp. 579-588
Author(s):  
Tatyana Ivanovska ◽  
Amro Daboul ◽  
Oleksandr Kalentev ◽  
Norbert Hosten ◽  
Reiner Biffar ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Soft Palate ◽  
High Speed ◽  
Sleep Apnea Syndrome ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Obstructive Sleep ◽  
Validation Set ◽  
Spine Mri

Abstract Purpose The main purpose of this work was to develop an efficient approach for segmentation of structures that are relevant for diagnosis and treatment of obstructive sleep apnea syndrome (OSAS), namely pharynx, tongue, and soft palate, from mid-sagittal magnetic resonance imaging (MR) data. This framework will be applied to big data acquired within an on-going epidemiological study from a general population. Methods A deep cascaded framework for subsequent segmentation of pharynx, tongue, and soft palate is presented. The pharyngeal structure was segmented first, since the airway was clearly visible in the T1-weighted sequence. Thereafter, it was used as an anatomical landmark for tongue location. Finally, the soft palate region was extracted using segmented tongue and pharynx structures and used as input for a deep network. In each segmentation step, a UNet-like architecture was applied. Results The result assessment was performed qualitatively by comparing the region boundaries obtained from the expert to the framework results and quantitatively using the standard Dice coefficient metric. Additionally, cross-validation was applied to ensure that the framework performance did not depend on the specific selection of the validation set. The average Dice coefficients on the test set were $$0.89\pm 0.03$$ 0.89 ± 0.03 , $$0.87\pm 0.02$$ 0.87 ± 0.02 , and $$0.79\pm 0.08$$ 0.79 ± 0.08 for tongue, pharynx, and soft palate tissues, respectively. The results were similar to other approaches and consistent with expert readings. Conclusion Due to high speed and efficiency, the framework will be applied for big epidemiological data with thousands of participants acquired within the Study of Health in Pomerania as well as other epidemiological studies to provide information on the anatomical structures and aspects that constitute important risk factors to the OSAS development.

scholarly journals Methods, Developments, and Technological Innovations for Population Surveys

2021 ◽  
pp. 089443932199421
Author(s):  
Venera Tomaselli ◽  
Sebastiano Battiato ◽  
Alessandro Ortis ◽  
Giulio G. Cantone ◽  
Salvatore Urso ◽  
...  
Keyword(s):  
Population Studies ◽  
Data Gathering ◽  
Computational Social Science ◽  
Technological Innovations ◽  
Computer Assisted ◽  
Respondent Driven Sampling ◽  
Population Surveys ◽  
Panel Management ◽  
Dominant Paradigm ◽  
Social Science Approach

This article reviews contemporary issues in survey research, connecting established methods to innovative tools and technologies like real-time sensors and computer vision. This link takes into account the idea about the “organical” nature of Big Data, which represents a challenge toward a modernization of population studies in the light of technological innovations. The adopted dominant paradigm of data gathering is web survey (computer-assisted web interviewing), which is explored through the formalization of chain-referral methods as respondent-driven sampling. The general orientation is toward a computational social science approach. Weaknesses of such methodology is studied and solutions are provided with insights from empirical research on panel management. Contribution from gamification techniques is critically discussed.

scholarly journals The Effect of Random Error in Exposure Measurement upon the Shape of the Exposure Response

Dose-Response ◽  
2005 ◽  
Vol 3 (4) ◽  
pp. dose-response.0 ◽  
Author(s):  
Kenny S. Crump
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Random Errors ◽  
Exposure Measurement ◽  
Considerable Uncertainty ◽  
Exposure Response ◽  
Log Normal ◽  
Normally Distributed

Although statistical analyses of epidemiological data usually treat the exposure variable as being known without error, estimated exposures in epidemiological studies often involve considerable uncertainty. This paper investigates the theoretical effect of random errors in exposure measurement upon the observed shape of the exposure response. The model utilized assumes that true exposures are log-normally distributed, and multiplicative measurement errors are also log-normally distributed and independent of the true exposures. Under these conditions it is shown that whenever the true exposure response is proportional to exposure to a power r, the observed exposure response is proportional to exposure to a power K, where K < r. This implies that the observed exposure response exaggerates risk, and by arbitrarily large amounts, at sufficiently small exposures. It also follows that a truly linear exposure response will appear to be supra-linear—i.e., a linear function of exposure raised to the K-th power, where K is less than 1.0. These conclusions hold generally under the stated log-normal assumptions whenever there is any amount of measurement error, including, in particular, when the measurement error is unbiased either in the natural or log scales. Equations are provided that express the observed exposure response in terms of the parameters of the underlying log-normal distribution. A limited investigation suggests that these conclusions do not depend upon the log-normal assumptions, but hold more widely. Because of this problem, in addition to other problems in exposure measurement, shapes of exposure responses derived empirically from epidemiological data should be treated very cautiously. In particular, one should be cautious in concluding that the true exposure response is supra-linear on the basis of an observed supra-linear form.

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