Computer methods and programs in biomedicine update最新文献

{"title":"Predicting Hypotensive Events in the ICU Settings Using Patient's Short-term Physiological History and Contextual Data","authors":"M. C. Moghadam, Ehsan Masoumi, S. Kendale, N. Bagherzadeh","doi":"10.1016/j.cmpbup.2023.100100","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2023.100100","url":null,"abstract":"","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49062274","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":"Evaluation of available risk scores to predict multiple cardiovascular complications for patients with type 2 diabetes mellitus using electronic health records","authors":"Joyce C Ho ,&nbsp;Lisa R Staimez ,&nbsp;K M Venkat Narayan ,&nbsp;Lucila Ohno-Machado ,&nbsp;Roy L Simpson ,&nbsp;Vicki Stover Hertzberg","doi":"10.1016/j.cmpbup.2022.100087","DOIUrl":"10.1016/j.cmpbup.2022.100087","url":null,"abstract":"<div><h3>Aims</h3><p>Various cardiovascular risk prediction models have been developed for patients with type 2 diabetes mellitus. Yet few models have been validated externally. We perform a comprehensive validation of existing risk models on a heterogeneous population of patients with type 2 diabetes using secondary analysis of electronic health record data.</p></div><div><h3>Methods</h3><p>Electronic health records of 47,988 patients with type 2 diabetes between 2013 and 2017 were used to validate 16 cardiovascular risk models, including 5 that had not been compared previously, to estimate the 1-year risk of various cardiovascular outcomes. Discrimination and calibration were assessed by the c-statistic and the Hosmer-Lemeshow goodness-of-fit statistic, respectively. Each model was also evaluated based on the missing measurement rate. Sub-analysis was performed to determine the impact of race on discrimination performance.</p></div><div><h3>Results</h3><p>There was limited discrimination (c-statistics ranged from 0.51 to 0.67) across the cardiovascular risk models. Discrimination generally improved when the model was tailored towards the individual outcome. After recalibration of the models, the Hosmer-Lemeshow statistic yielded p-values above 0.05. However, several of the models with the best discrimination relied on measurements that were often imputed (up to 39% missing).</p></div><div><h3>Conclusion</h3><p>No single prediction model achieved the best performance on a full range of cardiovascular endpoints. Moreover, several of the highest-scoring models relied on variables with high missingness frequencies such as HbA1c and cholesterol that necessitated data imputation and may not be as useful in practice. An open-source version of our developed Python package, cvdm, is available for comparisons using other data sources.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"3 ","pages":"Article 100087"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/b7/a4/nihms-1901943.PMC10274317.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9708383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming health systems with design health literacy: Presenting the 40-20-40 model for digital development","authors":"Lars Münter ,&nbsp;Danielle Drachmann ,&nbsp;Mouna Ghanem ,&nbsp;Yvonne Prinzellner ,&nbsp;Carolien Smits ,&nbsp;Katharina Werner ,&nbsp;Vera Bulsink ,&nbsp;Isabel Schwaninger ,&nbsp;Lex Van Velsen ,&nbsp;Nicolaj Holm Faber","doi":"10.1016/j.cmpbup.2023.100122","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2023.100122","url":null,"abstract":"<div><h3>Intro</h3><p>Digital tools and services are becoming the standard for delivery of health care, especially hastened by the restrictions and needs during the COVID-19 pandemic. While early experiences with telemedicine have been a foundation for modern day digital tool development, the use of co-creation, user meta dialogue, and follow up services are often short and few. This represents a powerful potential for designing upcoming services for a multi-level platform. This requires, however, equity in digital health literacy, which is often not the case. Rather than seeing effect or impact as the outcome of the service itself, the value of including and referencing user expectations before and after the session holds an even stronger value; therefore we've explored and created a new co-design approach to digital development we call the 40-20-40 model.</p></div><div><h3>Results</h3><p>Using the 40-20-40 approach we focus on early user communication and input as a part of the specific session or service design, a <em>prologue-phase</em>, that gathers vital input to align expectations. After the specific <em>intervention-phase</em>, we utilise the <em>epilogue-phas</em>e as an extension of the intervention itself, an echo of the prologue, and a gathering of user outcomes. We believe the pro- and epilogue phases represent a total of 80% of the overall impact of our services. We also argue that digital developers and public health service providers would benefit from a stronger use of this design model to improve the quality of care and the use and impact of care services, in particular for patients with limited digital health literacy.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"4 ","pages":"Article 100122"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49762643","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":"Multi-lead ECG heartbeat classification of heart disease based on HOG local feature descriptor","authors":"Mohammad Ali Sheikh Beig Goharrizi ,&nbsp;Amir Teimourpour ,&nbsp;Manijeh Falah ,&nbsp;Kiavash Hushmandi ,&nbsp;Mohsen Saberi Isfeedvajani","doi":"10.1016/j.cmpbup.2023.100093","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2023.100093","url":null,"abstract":"","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49780850","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":"Collection of patient-generated health data with a mobile application and transfer to hospital information system via QR codes","authors":"Chong Song ,&nbsp;Yoichi Kakuta ,&nbsp;Kenichi Negoro ,&nbsp;Rintaro Moroi ,&nbsp;Atsushi Masamune ,&nbsp;Erina Sasaki ,&nbsp;Naoki Nakamura ,&nbsp;Masaharu Nakayama","doi":"10.1016/j.cmpbup.2023.100099","DOIUrl":"10.1016/j.cmpbup.2023.100099","url":null,"abstract":"<div><h3>Background and Objective</h3><p>The collection of patient-generated health data (PGHD) is important for understanding a patient's daily status for efficient treatment. Mobile applications are effective for continuously collecting patient data, and it is desirable to promptly integrate such data into electronic medical records. However, most hospital information systems have limited connections with external mobile applications. Therefore, in this study, we developed a simple system that can collect data from patients with inflammatory bowel disease (IBD) and transfer the data to electronic medical records without a direct connection to a hospital information system.</p></div><div><h3>Methods</h3><p>We developed patient-facing mobile applications and physician-facing user-defined form templates for the hospital information system. The PGHD were transferred via QR codes using a two-way linkage. The persistence rates were measured and analyzed to clarify the factors affecting the continuous usage of the application.</p></div><div><h3>Results</h3><p>A mobile application connected to a hospital information system was implemented and used in on-site operations. Among patients with IBD using this application, 84.6%–91.7% continued to use it over six months and 72.2%–84.5% continued for over one year. Particularly, patients who used the application during the first two visits tended to be significantly frequent users.</p></div><div><h3>Conclusions</h3><p>We developed a mobile application connected to a hospital information system using a QR code, which is a simple way to continuously collect data from patients and enables physicians to use the data efficiently for patient-centered medical care.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"3 ","pages":"Article 100099"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43865598","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":"Examining the managerial and cost control for an optimal healthcare education","authors":"Emilio Abad-Segura ,&nbsp;Mariana-Daniela González-Zamar ,&nbsp;José Gómez-Galán","doi":"10.1016/j.cmpbup.2022.100088","DOIUrl":"10.1016/j.cmpbup.2022.100088","url":null,"abstract":"<div><p>In recent decades, both economic development and technological advances in medicine have contributed to an increase in health demand and costs, mainly derived from the growing implementation of innovative health services. In this context, it is necessary to note that welfare economics involves the rationalization of limited economic resources. Likewise, the concern about the increase in health spending that is occurring in developed countries has meant that hospitals have flexible management accounting that helps to maximize the efficiency of internal management and obtain the maximum performance of the allocated financial resources. This will have a favourable impact on indicators such as minimal infant mortality, increased life expectancy at birth, or the rate and effectiveness of transplants. Hence, organizations choose to improve their management systems to carry out a more efficient health care education, in such a way that these try to optimize the available resources to offer a quality product or service with the minimum possible costs. Bibliometric techniques have been applied to a sample of 2003 articles to establish the relationships between the main dynamic agents of this research topic, in addition to identifying the main current and future lines of research. Providing a benchmark for future research on management control for health care education, this study reveals the emerging intellectual structure of this interdisciplinary field.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"3 ","pages":"Article 100088"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44620355","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":"System for the analysis of human balance based on accelerometers and support vector machines","authors":"V.C. Pinheiro ,&nbsp;J.C. do Carmo ,&nbsp;F.A. de O. Nascimento ,&nbsp;C.J. Miosso","doi":"10.1016/j.cmpbup.2023.100123","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2023.100123","url":null,"abstract":"<div><p>Disturbances in balance control lead to movement impairment and severe discomfort, dizziness, vertigo and may also lead to serious accidents. It is important to monitor the level of balance in order to determine the risk of a fall and to evaluate progress during treatment. Some solutions exist, but they are generally restricted to indoor environments. We propose and evaluate a system, based on accelerometers and support vector machines, that indicates the user’s postural balance variation which can be used in indoor and outdoor environments. For the training phase of the system, we used the accelerometer signals acquired from a single subject under monitored conditions of balance and intentional imbalance, and used the scores provided by the SWAY®software for establishing the reference target values. Based on these targets, we trained a support vector machine to classify the signal into <span><math><mi>n</mi></math></span> levels of balance and later evaluated the performance using cross validation by random resampling. We also developed a support vector machine approach for estimating the center of pressure, by using as reference targets the results from a force platform. For validation, we performed experiments with a subject who was performing determined movements. Later other experiments were executed, so the different centers of pressure could be computed by our system and compared to the results from the force platform. We also performed tests with a dummy and a John Doe doll, in order to observe the system’s behavior in the presence of a sudden drop or a lack of balance. The results show that the system can classify the acquired signals into two to seven levels of balance, with significant accuracy, and was also able to infer the centroid of each center of pressure region with an error lower than 0.9 cm. The tests performed with the dolls show that the system is able to distinguish between the conditions of a sudden drop and of a recovery of balance after losing one’s balance. The results suggest that the system can be used to detect variations in balance and, therefore, to indicate the risk of a fall even in outdoor environments.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"4 ","pages":"Article 100123"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49727003","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":"Automated hair removal in dermoscopy images using shallow and deep learning neural architectures","authors":"Konstantinos Delibasis ,&nbsp;Konstantinos Moutselos ,&nbsp;Eleftheria Vorgiazidou ,&nbsp;Ilias Maglogiannis","doi":"10.1016/j.cmpbup.2023.100109","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2023.100109","url":null,"abstract":"","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"4 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49762627","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":"Improving automated thyroid cancer classification of frozen sections by the aid of virtual image translation and stain normalization","authors":"Michael Gadermayr ,&nbsp;Maximilian Tschuchnig ,&nbsp;Lea Maria Stangassinger ,&nbsp;Christina Kreutzer ,&nbsp;Sebastien Couillard-Despres ,&nbsp;Gertie Janneke Oostingh ,&nbsp;Anton Hittmair","doi":"10.1016/j.cmpbup.2023.100092","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2023.100092","url":null,"abstract":"","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49780849","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":"Using image processing and automated classification models to classify microscopic gram stain images","authors":"Kris Kristensen ,&nbsp;Logan Morgan Ward ,&nbsp;Mads Lause Mogensen ,&nbsp;Simon Lebech Cichosz","doi":"10.1016/j.cmpbup.2022.100091","DOIUrl":"10.1016/j.cmpbup.2022.100091","url":null,"abstract":"<div><h3>Background and Objective</h3><p>Fast and correct classification of bacterial samples are important for accurate diagnostics and treatment. Manual microscopic interpretation of Gram stain samples is both time consuming and operator dependent. The aim of this study was to investigate the potential for developing an automated algorithm for the classification of microscopic Gram stain images.</p></div><div><h3>Methods</h3><p>We developed and tested two algorithms (using image processing an Casual Probabilistic Network (CPN) and a Random Forest (RF) classification) for the automated classification of Gram stain images. A dataset of 660 images including 33 microbial species (32 bacteria and one fungus) was split into training, validation, and test sets. The algorithms were evaluated based on their ability to correctly classify samples and general characteristics such as aggregation and morphology.</p></div><div><h3>Results</h3><p>The CPN correctly classified 633/792 images to achieve an overall accuracy of 80% compared to the RF which correctly classified 782/792 images to achieve an overall accuracy of 99% (<em>p</em> &lt; 0.001). The CPN performed well when distinguishing between GN and GP, with an accuracy of 95% (731/768). The RF also performed well in distinguishing between GN and GP, achieving an accuracy of 99% (767/768) (<em>p</em> &lt; 0.001).</p></div><div><h3>Conclusions</h3><p>The findings from this study show promising results regarding the potential for an automated algorithm for the classification of microscopic Gram stain images.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"3 ","pages":"Article 100091"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46899539","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}