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2021 International Symposium on Biomedical Engineering and Computational Biology最新文献

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The study of variation in the Diagnostic Related Group Weight in a Complex Operative Units of Paediatrics and Paediatric Surgery due to CoViD-19 pandemic CoViD-19大流行对儿科和儿科外科复杂手术单位诊断相关组体重变化的研究
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3503659
I. Loperto, A. Borrelli, A. Lombardi, M. Triassi
{"title":"The study of variation in the Diagnostic Related Group Weight in a Complex Operative Units of Paediatrics and Paediatric Surgery due to CoViD-19 pandemic","authors":"I. Loperto, A. Borrelli, A. Lombardi, M. Triassi","doi":"10.1145/3502060.3503659","DOIUrl":"https://doi.org/10.1145/3502060.3503659","url":null,"abstract":"The CoViD-19 pandemic has unfortunately not spared the children. In most cases, the infection is asymptomatic and the serious outcomes are much lower than in adults. Despite this, as the hospital is committed to treating infected patients and limiting the spread of infections, pediatric surgery has also undergone the blocking of procedures deemed deferrable like other surgeries. In light of this, in this study it was decided to analyze how the activity of the Complex Operative Units (COUs) of Pediatrics and Pediatric Surgery in \"San Giovanni di Dio and Ruggi d'Aragona\" University Hospital of Salerno (Italy) was affected by the pandemic. Both statistical analysis and logistic regression show an increase of patients’ average age and of weight of Diagnostic Related Group (DRG).","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125828554","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}
引用次数: 0
Influence of demographic and organizational factors on the length of hospital stay in a general medicine department: Factors influencing length of stay in general medicine 人口统计学和组织因素对全科住院时间的影响:影响全科住院时间的因素
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3503652
Martina Profeta, G. Cesarelli, Cristiana Giglio, Giuseppe Ferrucci, A. Borrelli, Francesco Amato
{"title":"Influence of demographic and organizational factors on the length of hospital stay in a general medicine department: Factors influencing length of stay in general medicine","authors":"Martina Profeta, G. Cesarelli, Cristiana Giglio, Giuseppe Ferrucci, A. Borrelli, Francesco Amato","doi":"10.1145/3502060.3503652","DOIUrl":"https://doi.org/10.1145/3502060.3503652","url":null,"abstract":"Unnecessary Length of Hospital Stay (LOS) has significant consequences on the economy of the national healthcare system. Numerous factors may influence LOS, such as bad management of resources, beds and surgery procedures. In this work we investigate, among the demographic, clinical and organizational variables, those most affecting the LOS, through the use of Multiple Linear Regression model. Data of 262 patients were collected from the hospital information system of the General Medicine Department of the University L.P-o Hospital “San Giovanni di Dio and Ruggi d'Aragona” of Salerno. The regression model has been tested and optimized by selecting the most appropriate predictors and by finding the best trade-off between the number of independent variables and the absence of multicollinearity in the data. Results show that the variables influencing LOS were the gender, the number of procedures and the discharge modality.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129453085","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}
引用次数: 0
Logistic Regression to study the change in length of stay in a department of Ophthalmology in CoViD-19 era Logistic回归分析2019冠状病毒病疫情时期某眼科住院时间的变化
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3503660
A. Scala, R. Alfano, A. Borrelli, Giovanni Rossi, M. Triassi
{"title":"Logistic Regression to study the change in length of stay in a department of Ophthalmology in CoViD-19 era","authors":"A. Scala, R. Alfano, A. Borrelli, Giovanni Rossi, M. Triassi","doi":"10.1145/3502060.3503660","DOIUrl":"https://doi.org/10.1145/3502060.3503660","url":null,"abstract":"The CoViD-19 pandemic since December 2019 has rapidly spread around the world and to date does not seem to stop its run. The world has paid a very high price in terms of human lives lost and economic repercussions. Health systems have generally been severely tested. The strong demand for CoViD-19 patients has resulted in the blocking of deferred elective procedures and a reconversion of beds and human and technological resources towards the management of the pandemic. In this work, the activity of the Department of Ophthalmology in \"San Giovanni di Dio and Ruggi d'Aragona\" University Hospital of Salerno (Italy) was analyzed. Specifically, the value obtained from a set of data in the year 2019 (pre-pandemic) was compared with that obtained in the following year, in the height of the pandemic. The results show that patients admitted in 2020 have a shorter length of stay.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126531573","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}
引用次数: 3
Analysis of Personal Dosimetry and Assistance to Patients at a Radiation Therapy Clinic, to Assign Vacation to Exposed Occupational Workers, using Circular Data Analysis 使用循环数据分析分析放射治疗诊所的个人剂量测定和对病人的帮助，为受照射的职业工人分配假期
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3502324
Erick Estuardo Hernandez, Mansilla Ximena, Omar Chanta
{"title":"Analysis of Personal Dosimetry and Assistance to Patients at a Radiation Therapy Clinic, to Assign Vacation to Exposed Occupational Workers, using Circular Data Analysis","authors":"Erick Estuardo Hernandez, Mansilla Ximena, Omar Chanta","doi":"10.1145/3502060.3502324","DOIUrl":"https://doi.org/10.1145/3502060.3502324","url":null,"abstract":"Results of personal dosimetry from occupationally exposed workers were analyzed, as well as the demand for treatments on a radiotherapy clinic. This data was used to determine the optimal time interval to assign vacations to the workers, to optimize patient attention without affecting permissible personal dosimetry of those who work on said vacations. Circular data analysis was used for both samples, to determine the concentration of data on certain months of the year for the corresponding decision making. The results obtained in the present study allow the assignation of vacations for these personnel, optimizing the personal dosimetry during this time and the efficient patient attention.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130896329","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}
引用次数: 0
Sapindus saponins inhibits tyrosinase & Glutathione-induced melanin deposition by obstructing DOPA and cysteyl derivatives transformation pathways 皂素通过阻断多巴和半胱氨酸衍生物转化途径抑制酪氨酸酶和谷胱甘肽诱导的黑色素沉积
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3502146
Kang Jin, Yunpeng Sun, Shengxue Zhou
{"title":"Sapindus saponins inhibits tyrosinase & Glutathione-induced melanin deposition by obstructing DOPA and cysteyl derivatives transformation pathways","authors":"Kang Jin, Yunpeng Sun, Shengxue Zhou","doi":"10.1145/3502060.3502146","DOIUrl":"https://doi.org/10.1145/3502060.3502146","url":null,"abstract":"Background/Objective: The ancient Chinese book, the Compendium of Materia Medica, records that the peel of Sapindus whitens and protects the skin. This study focused on the removal of melanin by Sapindus saponins and determining the involvement of TYR & GSH pathways. Methods: The inhibition rate of Sapindus saponins on TYR activity was measured in vitro. SOD, MDA, TYR and GSH levels in mice were measured, and the amount of melanocytes and melanin in the epidermal cells were analyzed microscopically to evaluate the scavenging effect of Sapindus saponins on melanin in vivo. The expression of TYR, TRP-1, and TRP-2 was examined by western blot. Results: Higher inhibition rate (48.69%) was achieved by PIVb and 40% TYR inhibition rate by SA and SB at 1 mg.mL-1. The SOD content could be significantly enhanced and the MDA, TYR and GSH content were decreased by PIVb, SA, and SB. The melanin in PIVb, SA, and SB-treated groups showed a trend of desalination following epidermal cell analysis. In the expression of TYR, TRP-1 and TRP-2, PIVB also played the very important role to reduce the proteins levels. Conclusions: PIVb, SA, and SB in Sapindus saponins exerted effects of melanin clearance and TRY inhibition evidenced by the amount of melanocytes and melanin in the epidermal cells, alleviation of TYR & GSH pathways-mediated melanin deposition, while PIVb had a stronger effect than SA and SB, showing potential as a good candidate for treating melanosis.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131253822","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}
引用次数: 0
Use of statistical analysis and logistic regression to study the length of stay in an Emergency Medicine Department in CoViD-19 era 应用统计分析和logistic回归研究新冠肺炎疫情下急诊科住院时间
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3503661
I. Loperto, Lucia De Coppi, A. Scala, A. Borrelli, Giuseppe Ferrucci, M. Triassi
{"title":"Use of statistical analysis and logistic regression to study the length of stay in an Emergency Medicine Department in CoViD-19 era","authors":"I. Loperto, Lucia De Coppi, A. Scala, A. Borrelli, Giuseppe Ferrucci, M. Triassi","doi":"10.1145/3502060.3503661","DOIUrl":"https://doi.org/10.1145/3502060.3503661","url":null,"abstract":"Since the first case recorded in China in 2019, CoViD-19 has overwhelmed the health systems of all countries. The highly complex request for assistance combined with the fear of contagion have changed the normal activity of hospitals. Conversely, as the pandemic spreads, fewer people are going to the Emergency Department (ED) for non-CoViD diseases. In this study, logistic regression and statistical analysis were used to investigate how the pandemic changed the activity of the Emergency Medicine Department of \"San Giovanni di Dio and Ruggi d'Aragona\" University Hospital of Salerno (Italy). Patients admitted in 2020 have a higher Length of Stay (LOS) and the mode of discharge is mostly \"at home\". While the discharge modality 'transferred to another regime in the same hospital' had significantly decreased in order to counter the internal contagion.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128487090","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}
引用次数: 1
Comparison of machine learning algorithms to predict length of hospital stay in patients undergoing heart bypass surgery 预测心脏搭桥手术患者住院时间的机器学习算法比较
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3503625
Martina Profeta, A. M. Ponsiglione, C. Ponsiglione, Giuseppe Ferrucci, Cristiana Giglio, A. Borrelli
{"title":"Comparison of machine learning algorithms to predict length of hospital stay in patients undergoing heart bypass surgery","authors":"Martina Profeta, A. M. Ponsiglione, C. Ponsiglione, Giuseppe Ferrucci, Cristiana Giglio, A. Borrelli","doi":"10.1145/3502060.3503625","DOIUrl":"https://doi.org/10.1145/3502060.3503625","url":null,"abstract":"Patients affected by coronary artery obstruction, generally undergo aortocoronary bypass, an open-heart surgery that considerably affect health care expenditure. Since that, the monitoring and government of Aortocoronary bypass performance may be of help in health care management. In this work we compare various machine learning-based classification algorithms, to determine the length of stay for aortocoronary bypass. Data were collected on a group of 116 patients of the “San Giovanni di Dio e Ruggi D'Aragona” University Hospital of Salerno (Italy). Different socio-demographic, clinical, and organizational factors were taken into consideration as input parameters of the model for carrying out the classification analysis. The predictive capability of each of the tested machine learning algorithms was assessed in terms of accuracy and error percentages in the classification and obtained results were compared. Among the adopted algorithms, the Random Forest showed far better performances than the other ones, with an accuracy level of around 97%, thus potentially suggesting the Random Forest as a reliable predictive tool in the determination of the length of hospital stay of healthcare data for patients undergoing coronary artery bypass surgery.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130563897","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}
引用次数: 10
Modeling the variation in length of stay for appendectomy and cholecystectomy interventions in the emergency general surgery 急诊普通外科手术中阑尾切除术和胆囊切除术干预措施住院时间变化的建模
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3503651
A. M. Ponsiglione, Martina Profeta, Cristiana Giglio, A. Lombardi, A. Borrelli, A. Scala
{"title":"Modeling the variation in length of stay for appendectomy and cholecystectomy interventions in the emergency general surgery","authors":"A. M. Ponsiglione, Martina Profeta, Cristiana Giglio, A. Lombardi, A. Borrelli, A. Scala","doi":"10.1145/3502060.3503651","DOIUrl":"https://doi.org/10.1145/3502060.3503651","url":null,"abstract":"Emergency general surgery can often represent a challenge in the clinical practice. This is partially due to the annual growth in the overall number of hospital admissions, especially in developed countries, and to the increasing percentage of elderly patients requiring care procedures. In literature, it is known that, when compared to the elective surgical interventions, the procedures in the emergency general surgery are characterized by a significantly higher morbidity and mortality rates and, not least prolonged length of stay (LOS), which constitutes a relevant metric reflecting both the patient satisfaction and the overall quality of the health services. In this paper, we sought to investigate on length of stay (LOS) variation for appendectomy and cholecystectomy interventions in the emergency general surgery by using a multiple regression analysis, with the purpose of identifying those factors that have the highest contribution in increasing the LOS.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130810394","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}
引用次数: 3
Use of regression models to predict glomerular filtration rate in kidney transplanted patients 应用回归模型预测肾移植患者肾小球滤过率
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3503627
I. Loperto, A. Scala, Lucia Rossano, R. Carrano, S. Federico, M. Triassi, G. Improta
{"title":"Use of regression models to predict glomerular filtration rate in kidney transplanted patients","authors":"I. Loperto, A. Scala, Lucia Rossano, R. Carrano, S. Federico, M. Triassi, G. Improta","doi":"10.1145/3502060.3503627","DOIUrl":"https://doi.org/10.1145/3502060.3503627","url":null,"abstract":"Despite of the numerous progress of modern medicine, organ transplantation is never a free risk procedure. Kidney transplant, in particular, can bring to numerous short and/or long-term problems, like infection or diabetes. Since such problems can appear up to years, a constant monitoring of Kidney transplanted patients is necessary to try and avoid a bad prognosis. Glomerular Filtration rate (GFR) is an important marker to evaluate kidney transplanted patients. Since it is necessary to measure values of GFR over time, new predictive approaches can reveal useful to such scope. In this work we present a Multiple Linear Regression model and a Machine Learning method to correlate GFR with glycaemia (mg/dL) and the dosage of a calcineurin inhibitor. Results show how such model can be useful in a long term evaluation of kidney transplanted patients.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126296879","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}
引用次数: 2
Extraction and Evaluation of EEG Covariates and Their Influence on GLM Model: EEG covariates and their influence on GLM model 脑电协变量的提取与评价及其对GLM模型的影响:脑电协变量及其对GLM模型的影响
2021 International Symposium on Biomedical Engineering and Computational Biology Pub Date : 2021-08-13 DOI: 10.1145/3502060.3502354
V. Piorecká, F. Černý, M. Piorecký, V. Koudelka, J. Horáček, J. Bušková, M. Brunovský, J. Kopřivová
{"title":"Extraction and Evaluation of EEG Covariates and Their Influence on GLM Model: EEG covariates and their influence on GLM model","authors":"V. Piorecká, F. Černý, M. Piorecký, V. Koudelka, J. Horáček, J. Bušková, M. Brunovský, J. Kopřivová","doi":"10.1145/3502060.3502354","DOIUrl":"https://doi.org/10.1145/3502060.3502354","url":null,"abstract":"This study aims at the identification of suitable approaches to dimension reduction methods for EEG covariate extraction for GLM analysis of fMRI time series. We present the results of anatomical and mathematical methods of dimension covariate reduction and their combinations. Individual models according to the used covariates showed that jPCA creates a lower number of significantly correlated voxels. Anatomical reduction balances the number of correlated voxels between mean and jPCA. The choice of covariates has a significant effect on the resulting GLM activations. The average allows generalization to explain a physiological activity, jPCA offers the ability to identify specific activations.","PeriodicalId":193100,"journal":{"name":"2021 International Symposium on Biomedical Engineering and Computational Biology","volume":"287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121069935","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}
引用次数: 0
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