R. Radakovic, Nikola Jankovic, Jelica Dimitrijević, Nataša Zdravković Petrović, Aleksandra Vulovic, N. Filipovic
{"title":"Analysis of forces in knee joints of top football players and futsal players in different types of jumps","authors":"R. Radakovic, Nikola Jankovic, Jelica Dimitrijević, Nataša Zdravković Petrović, Aleksandra Vulovic, N. Filipovic","doi":"10.1109/BIBE52308.2021.9635362","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635362","url":null,"abstract":"In this paper, we will consider the forces in knee joints in football and futsal players during different types of jumps. We will consider two types of jumps: jumps with flywheel and jumps without flywheel. This study has two main aims. The first aim is to compare the knee joint forces in football players and futsal players during different types of jumps. The second aim is to determine the distribution of deformation and stress in menisci of the knee joints in football and futsal players. Professional futsal players performed jumps that were analyzed using a force plate and high-speed video camera system. For this purpose, a 3D model of the human knee joint was developed from medical scans. The 3D model of the human knee joint consisted of femur, fibula, tibia, articular cartilage, ligaments and menisci. Loads and material characteristics were adopted from the literature. The use of finite elements analysis enabled us to gain better understanding of the distribution of deformation and stress in specific parts of the knee joint, with the special focus on the menisci.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127484207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Šušteršič, Vesna Ranković, Vojin Kovacevic, Vladimir M. Milovanović, L. Rasulić, N. Filipovic
{"title":"Machine Learning-based Image Processing in Support of Discus Hernia Diagnosis","authors":"T. Šušteršič, Vesna Ranković, Vojin Kovacevic, Vladimir M. Milovanović, L. Rasulić, N. Filipovic","doi":"10.1109/BIBE52308.2021.9635305","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635305","url":null,"abstract":"Diagnosing lumbar discus hernia is a challenging task, due to disc and vertebral variations in size, shape, quantity, and appearance. Medical history and physical examination, electrodiagnostic tests, and MRIs are all used by doctors to set a definitive diagnosis. A majority of the state-of-the-art methods are semi-automatic and require extra corrections to the solution or are extremely sensitive to changes in parameters. Based on literature review, there is a solid basis for implementation of machine learning-based methods for disc herniation detection in MRI images. An automated segmentation method of vertebrae and discs is proposed in this study as a first step towards a decision support system for discus hernia identification. Dataset consisted of 104 images in sagittal and 99 images in axial views. Optimized convolutional neural network U-net has demonstrated very high accuracy in segmentation. Additional result represents the calculated distance from the disc's center to the disc's edge points in axial images across 360°, which results in clearly different number of peaks for the healthy and diseased discs. Fully automated computer diagnostic system helps speed up the process of setting up adequate diagnosis and reducing human mistakes.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125349505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Influence of M-cells on the generation of re-entry in Short QT Syndrome","authors":"P. Priya, Srinivasan Jayaraman","doi":"10.1109/BIBE52308.2021.9635264","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635264","url":null,"abstract":"The distribution of M-cells have always been vital in creating intrinsic spatial heterogeneity thereby acting as a substrate for the development and maintenance of re-entry. Here, a 2D anisotropic transmural tissue made up of endocardial (endo), midmyocardial (mid) and epicardial (epi) layers was constructed by using the ventricular cell model developed by Ten Tusscher et al. Two configurations, the entire column of mid layer and an island within the mid layer of the tissue were considered as M cells. In the latter configuration, slight alterations were introduced in the slow delayed rectifying potassium current and the outward transient current so that the APD is highest in the M-cells followed by the endo, mid and epi cells. The likelihood of reentry generation under conditions of KCNQ1-linked Short QT syndrome type 2 (SQTS2) was then analysed in these two types of tissue configurations. Simulation results show that on including SQTS2 conditions and on pacing the tissue with premature beats in between normal beats, re-entrant waves were generated in the tissue containing a column of M - cells whereas in the tissue including the M-cell island, re-entry was not generated. This study is not in line with those reported earlier due to the variations in the size of the chosen M -cell island as well as the cellular electrophysiological properties. From this investigation, the need for further analysis on the size, location as well as the ionic properties of the M-cells in relation to the neighbouring cells has been emphasized.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131792099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Preliminary study for a fully automated pre-gating method for high-dimensional mass cytometry data","authors":"A. Suwalska, J. Polańska","doi":"10.1109/BIBE52308.2021.9635492","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635492","url":null,"abstract":"Mass cytometry as an advanced single-cell analysis technology can produce high-dimensional data consisting of millions of cells and more than 50 features. Therefore the cell subtypes identification is difficult and impossible to be done manually. Each step of the analysis affect the results and may cause a loss of rare sub-populations of interest. One of the first steps in the analysis is pre-gating which involves filtering out unwanted measurements like debris or doublets. The existing semi-automated solutions for pre-gating require some parameters to be set which may lead to different results. Moreover, the tools often use downsampling from millions to thousands of cells. Despite the existing methods, there is still a need for a fully automated tool that will be independent of sample size. In the study, we developed a solution based on Gaussian Mixture Model (GMM) decomposition and grouping of its components into clusters. Based on the clusters we propose filtration criteria that identify measurements to be removed from the analysis. The algorithm was validated on two independent public datasets. The results are promising and reproducible, leaving intact, live cells that can be further analyzed.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132528542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Draginic, M. Andjic, V. Zivkovic, Kristina Radoman, M. Nikolić, Maja Savić, A. M. Samanovic, S. Bolevich, V. Jakovljevic
{"title":"The impact of chronic administration of evening primrose oil and flaxseed oil on redox status of male and female Wistar albino rats","authors":"N. Draginic, M. Andjic, V. Zivkovic, Kristina Radoman, M. Nikolić, Maja Savić, A. M. Samanovic, S. Bolevich, V. Jakovljevic","doi":"10.1109/BIBE52308.2021.9635420","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635420","url":null,"abstract":"Taken into consideration that oxidative stress response to flaxseed (FSO) and evening primrose oil (EPO) has still not been clarified, the aim of this study was to assess the effects of these two oils, rich in omega-3 and omega-6 polyunsaturated fatty acids on systemic redox status in male and female Wistar albino rats. The study was carried out on 60 Wistar albino rats classified into two groups, male and female rats. Both groups were divided into three subgroups according to applied oil. The first subgroup was control group, without treatment. The second and third subgroups included animals treated with FSO or EPO in a dose of 300mg/kg/day and 10mg/kg/day per os, respectively. After 6 weeks of treatment, the animals were sacrificed. Following pro-oxidative markers were measured spectrophotometrically from plasma samples: nitrites (NO2-), superoxide anion radical (02-), hydrogen peroxide (H2O2), index of lipid peroxidation (TBARS). Parameters of antioxidant protection were measured from erythrocyte lysate: superoxide dismutase (SOD), catalase (CAT), and reduced glutathione (GSH). No significant gender specific differences in pro-oxidant markers were noticed in between EPO and FSO groups (p>0.05). Both EPO and FSO significantly increased SOD and GSH compared to CTRL in both genders (p<0.05), while FSO improved CAT values only in males, and EPO only in females. Chronic administration of EPO and FSO omega 3and 6 rich plant oils improved antioxidant defense system with slight gender specific differences in CAT. It's effect on pro-oxidants didn't seem to be protective.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134588474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nathan Siu, Maxime Ruiz, Sheyla González Garrido, Yu Yan, Dylan Steinecke, Elizabeth Rao, Rachel Choi, S. Robertson, S. Deng, C. Arnold, W. Speier
{"title":"Automatic Estimation of Limbal Stem Cell Densities in Cultured Epithelial Cell Microscopy Imaging","authors":"Nathan Siu, Maxime Ruiz, Sheyla González Garrido, Yu Yan, Dylan Steinecke, Elizabeth Rao, Rachel Choi, S. Robertson, S. Deng, C. Arnold, W. Speier","doi":"10.1109/BIBE52308.2021.9635557","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635557","url":null,"abstract":"Limbal stem cell deficiency (LSCD) is a progressive corneal disease that renders the corneal epithelium unable to repair itself, which can lead to the eventual loss of vision. Advances in technology have allowed for the growth of limbal stem cells ex-vivo for the purposes of transplantation. One method used to evaluate the quality of these cultivated cells is cell density, which is typically calculated manually by experts, which is time-consuming and has high inter-rater variability. The goal of this project was to create a tool that automatically calculates cell density from digital images of the cultured cells. Results were compared against annotations from four experts with varying levels of experience. Cell counts had high correlation with expert annotations (r=0.64, p<0.01). When compared to human annotators with lower clinical experience, the algorithm achieved significantly better agreement with highly experienced annotators (r=0.75 vs r=0.19, p<0.01). These results suggest that the automated tool can provide meaningful cell density counts, which can potentially improve annotation consistency and reduce time required for evaluating LSCD cell cultures.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133597672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Leung, Thanh Huy Daniel Mai, N. D. Tran, Christine Y. Zhang
{"title":"Predictive Analytics to Support Health Informatics on COVID-19 Data","authors":"C. Leung, Thanh Huy Daniel Mai, N. D. Tran, Christine Y. Zhang","doi":"10.1109/BIBE52308.2021.9635556","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635556","url":null,"abstract":"Bioinformatics and health informatics-in conjection with data science, data mining and machine learning-have been applied in numerous real-life applications including disease and healthcare analytics, such as predictive analytics of coronavirus disease 2019 (COVID-19). Many of these existing works usually require large volumes of data train the classification and prediction models. However, these data (e.g., computed tomography (CT) scan images, viral/molecular test results) that can be expensive to produce and/or not easily accessible. For instance, partially due to privacy concerns and other factors, the volume of available disease data can be limited. Hence, in this paper, we present a predictive analytics system to support health analytics. Specifically, the system make good use of autoencoder and few-shot learning to train the prediction model with only a few samples of more accessible and less expensive types of data (e.g., serology/antibody test results from blood samples), which helps to support prediction on classification of potential patients (e.g., potential COVID-19 patients). Moreover, the system also provides users (e.g., healthcare providers) with predictions on hospitalization status and clinical outcomes of COVID-19 patients. This provides healthcare administrators and staff with a good estimate on the demand for healthcare support. With this system, users could then focus and provide timely treatment to the true patients, thus preventing them for spreading the disease in the community. The system is helpful, especially for rural areas, when sophisticated equipment (e.g., CT scanners) may be unavailable. Evaluation results on a real-life datasets demonstrate the effectiveness of our digital health system in health analytics, especially in classifying patients and their medical needs.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133456994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cost-effectiveness analysis of in silico clinical trials of vascular stents","authors":"M. Gacic, Milica Kaplarevic, N. Filipovic","doi":"10.1109/BIBE52308.2021.9635321","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635321","url":null,"abstract":"The world stent market has an estimated value of €6.4 billion, of which 37% is generated in the US and 10% in the EU. Coronary stents are now the most commonly implanted medical devices, with more than 1 million implanted annually. Coronary stents are currently the most widely used for treating symptomatic coronary disease. In this study, the traditional approach for today's clinical trials with only 10% success rate was described. Within the EU funded project InSilc (www.insilc.eu) was developed the innovative platform for designing, developing and assessing coronary stents. It consists of separate modules and some of them can be used as a standalone tool. Description of each module was given. Cost-effectiveness analysis described the calculation method of the prices of each module as well as platform as a whole, per one stent simulation. The average cost per patient for the execution of a real clinical trial was calculated. The calculated price for in silico trials is below breakeven point in comparison to real clinical trial.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117237692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detecting attention in Hilbert-transformed EEG brain signals from simple-reaction and choice-reaction cognitive tasks","authors":"P. Dzianok, M. Kołodziej, E. Kublik","doi":"10.1109/BIBE52308.2021.9635187","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635187","url":null,"abstract":"The aim of this study was to investigate supervised machine learning approaches for detecting attentive brain states in the electroencephalogram (EEG) signal. EEG was recorded during methodologically similar tasks with different attentional loads: choice-reaction task (CRT) and simple-reaction task (SRT). This approach minimalizes the influence of other cognitive processes or motor preparation on classification results and thus shows the real discrimination of attentive states. We applied a Hilbert transformation to single trial EEG data to extract selected signal features and then compared the effectiveness of three classifiers: Extra Trees (ET), Support vector machines (SVM) and logistic regression; as well as two methods of feature selection: an ANOVA-based method and Sequential backward floating selection (SBFS). ET and SVM classifiers and logistic regression yielded similar classification results. Classification accuracy was up to 100% for individual subjects and 89% was the average classification accuracy for all subjects after SBFS with the use of ET and logistic regression. ET achieved the highest precision (91%) and specificity (91 %), whereas highest sensitivity (89%) was observed for LR.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133317090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Ge, H. Saeidi, M. Kam, J. Opfermann, A. Krieger
{"title":"Supervised Autonomous Electrosurgery for Soft Tissue Resection","authors":"J. Ge, H. Saeidi, M. Kam, J. Opfermann, A. Krieger","doi":"10.1109/BIBE52308.2021.9635563","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635563","url":null,"abstract":"Surgical resection is the current clinical standard of care for treating squamous cell carcinoma. Maintaining an adequate tumor resection margin is the key to a good surgical outcome, but tumor edge delineation errors are inevitable with manual surgery due to difficulty in visualization and hand-eye coordination. Surgical automation is a growing field of robotics to relieve surgeon burdens and to achieve a consistent and potentially better surgical outcome. This paper reports a novel robotic supervised autonomous electrosurgery technique for soft tissue resection achieving millimeter accuracy. The tumor resection procedure is decomposed to the subtask level for a more direct understanding and automation. A 4-DOF suction system is developed, and integrated with a 6-DOF electrocautery robot to perform resection experiments. A novel near-infrared fluorescent marker is manually dispensed on cadaver samples to define a pseudotumor, and intraoperatively tracked using a dual-camera system. The autonomous dual-robot resection cooperation workflow is proposed and evaluated in this study. The integrated system achieves autonomous localization of the pseudotumor by tracking the near-infrared marker, and performs supervised autonomous resection in cadaver porcine tongues (N =3). The three pseudotumors were successfully removed from porcine samples. The evaluated average surface and depth resection errors are 1.19 and 1.83mm, respectively. This work is an essential step towards autonomous tumor resections.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122621471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}