Computer methods and programs in biomedicine update最新文献

{"title":"Concepts, objectives and analysis of public health surveillance systems","authors":"Hurmat Ali Shah,&nbsp;Mowafa Househ","doi":"10.1016/j.cmpbup.2024.100136","DOIUrl":"10.1016/j.cmpbup.2024.100136","url":null,"abstract":"<div><p>Public health surveillance (PHS) systems are an important tool to map the distribution and burden of disease as well as enable efficient distribution of resources to fight a disease. The surveillance systems are used to detect, report, track a disease as well as assess the response to the disease and people's attitudes. PHS systems are changing with the rapid change in technology and are becoming more real-time responsive with availability of new type of data such as online content and social media data. This review presents the basics of surveillance systems and develop from it to show the evolution of surveillance systems. The different forms of data available, surveillance methods and surveillance types are also reviewed such as social media based, web-based and clinical data based PHS maps. This review provide comprehensive details of the surveillance systems in terms of data types used, source of data and purpose of the surveillance system.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"5 ","pages":"Article 100136"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266699002400003X/pdfft?md5=c7174d19610aa51e76061c94d0b56e24&pid=1-s2.0-S266699002400003X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139456573","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":"ResfEANet: ResNet-fused External Attention Network for Tuberculosis Diagnosis using Chest X-ray Images","authors":"Chukwuebuka Joseph Ejiyi ,&nbsp;Zhen Qin ,&nbsp;Ann O Nnani ,&nbsp;Fuhu Deng ,&nbsp;Thomas Ugochukwu Ejiyi ,&nbsp;Makuachukwu Bennedith Ejiyi ,&nbsp;Victor Kwaku Agbesi ,&nbsp;Olusola Bamisile","doi":"10.1016/j.cmpbup.2023.100133","DOIUrl":"10.1016/j.cmpbup.2023.100133","url":null,"abstract":"<div><p>Pulmonary tuberculosis (TB), the most prevalent form of TB, remains a major global public health concern, contributing to more than a million deaths each year. The accurate and timely diagnosis of this disease is of paramount importance for effective control and treatment. Chest X-ray (CXR) images have emerged as a valuable tool for screening lung diseases, including TB, owing to their cost-effectiveness and non-invasiveness. Despite advancements in technology, the challenges associated with interpreting CXR images persist, primarily due to the scarcity of trained radiologists. This underscores the pressing need for an automated and cost-effective computer-aided system capable of diagnosing TB, assisting medical practitioners in distinguishing between TB-positive and negative CXR scans. In response to this need, we introduce an innovative approach called ResNet-fused External Attention Network (ResfEANet). This network excels in accurately classifying TB from CXR images, achieving remarkable levels of accuracy and sensitivity. ResfEANet is built upon ResNet and incorporates an External Attention mechanism, albeit with fewer residual network blocks than ResNet-50 resulting in a relatively shallow network with fewer layers. This approach proves highly effective in feature extraction and yields competitive results in the classification of TB. Our method was employed to train a model that demonstrated an impressive accuracy rate of 97.59% and a remarkable sensitivity of 100% in binary classification tasks with optimal computational cost. These outcomes suggest that our proposed approach has the potential to serve as a valuable secondary tool in clinical decision-making, providing crucial assistance to radiologists and healthcare professionals.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"5 ","pages":"Article 100133"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666990023000411/pdfft?md5=81aecaa858595c69800e5427f5591e96&pid=1-s2.0-S2666990023000411-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139193821","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":"Mathematical modeling of the effects of vector control, treatment and mass awareness on the transmission dynamics of dengue fever","authors":"Boniface Zacharia Naaly ,&nbsp;Theresia Marijani ,&nbsp;Augustino Isdory ,&nbsp;Jufren Zakayo Ndendya","doi":"10.1016/j.cmpbup.2024.100159","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2024.100159","url":null,"abstract":"<div><p>Dengue fever is a vital public health concern that affects about 40% of the world’s population. To address the dynamics of dengue disease, a mathematical model was formulated by incorporating three control strategies: vector control, treatment, and mass awareness. A stability analysis of the disease-free equilibrium (DFE) was conducted using the Jacobian matrix. The DFE was found to be locally and globally asymptotically stable when the effective reproductive number was less than one; otherwise, it was unstable. Additionally, an endemic equilibrium point (EEP) was identified. The global stability analysis of the EEP, performed using the Lyapunov method, showed that it is globally asymptotically stable whenever <span><math><mrow><msub><mrow><mi>R</mi></mrow><mrow><mi>e</mi></mrow></msub><mo>&gt;</mo><mn>1</mn></mrow></math></span>; otherwise, it is unstable. Bifurcation analysis revealed that the model system exhibits a forward bifurcation. Furthermore, sensitivity analysis of the effective reproduction number revealed that the most sensitive parameters are the biting rate (<span><math><mi>b</mi></math></span>) and insecticide efficacy (<span><math><mi>δ</mi></math></span>). Therefore, the results suggest that, in order to reduce new dengue cases, intervention strategies that decrease the biting rate, such as mosquito repellents and the use of insecticides to kill mosquitoes, should be implemented. Moreover, simulations were conducted for the extended model with vector control, treatment, and mass awareness. The results showed that the combination of vector control, treatment, and mass awareness has a more positive impact on the control of dengue fever than any single or paired intervention. Thus, for effective control of dengue fever, the three control measures should be implemented simultaneously, especially in endemic areas.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"6 ","pages":"Article 100159"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666990024000260/pdfft?md5=58dbf14090021c1ebf275bc2a8944acb&pid=1-s2.0-S2666990024000260-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141480951","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":"Pediatric resident use, perceptions, and desires for improvement of a clinical secure messaging application","authors":"Andrew W Halterman ,&nbsp;Anneli R Cochrane ,&nbsp;Andrew D Miller ,&nbsp;Joy L Lee ,&nbsp;William E Bennett Jr ,&nbsp;Emily L Mueller","doi":"10.1016/j.cmpbup.2024.100162","DOIUrl":"10.1016/j.cmpbup.2024.100162","url":null,"abstract":"<div><h3>Background</h3><p>Hospitals are transitioning away from traditional pagers to secure text messaging (STM) applications. STM is perceived to improve efficiency and accessibility. There is limited research on user's impressions of how STM impacts patient safety, provider wellness, and quality of patient care.</p></div><div><h3>Objectives</h3><p>To understand the use and perceptions of a clinical STM by pediatric residents at a free-standing quaternary care children's hospital.</p></div><div><h3>Methods</h3><p>A survey was conducted of pediatric residents regarding their experience with Diagnotes®. Demographic data were obtained along with use patterns, ability to perform tasks, and perceptions of intended purpose. Further questions evaluated agreement with communication strategies and satisfaction with features. Three open-ended questions asked about experience where STM impacted (1) patient care coordination and (2) patient safety. A final question asked for any additional STM feedback.</p></div><div><h3>Results</h3><p>Of 169 surveys, there were 112 respondents (66.3 % response rate). Respondents unanimously endorsed daily STM use on their personal mobile devices with good knowledge of basic features. Respondents were overall satisfied with Diagnotes® (73.9 %) including the ability to communicate efficiently (84.8 %) and effectively (79.5 %). Yet only 32.1 % were satisfied with Diagnotes® training. Only 59.5 % believed Diagnotes® was appropriate for urgent patient care needs and only 43.2 % believed its purpose was to inform the team of patient emergencies. Key qualitative themes included improved coordination of patient care tasks through STM, but there were concerns raised around sending and receiving messages, the additional cognitive burden placed by STM, and differences in culture of use that created conflict.</p></div><div><h3>Conclusions</h3><p>Diagnotes® is viewed positively including use for effective coordination of patient care and familiarity of functions of Diagnotes®. Barriers included unclear interprofessional expectations for use. Future research should incorporate a broad range of healthcare professionals' perceptions and co-creation of STM best practice guidelines for use, including around urgent or emergent patient care issues.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"6 ","pages":"Article 100162"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666990024000296/pdfft?md5=fffb03e6fa793fc16f6f7fde766689f3&pid=1-s2.0-S2666990024000296-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142136478","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":"Machine learning from real data: A mental health registry case study","authors":"Elisabetta Gentili ,&nbsp;Giorgia Franchini ,&nbsp;Riccardo Zese ,&nbsp;Marco Alberti ,&nbsp;Maria Ferrara ,&nbsp;Ilaria Domenicano ,&nbsp;Luigi Grassi","doi":"10.1016/j.cmpbup.2023.100132","DOIUrl":"10.1016/j.cmpbup.2023.100132","url":null,"abstract":"<div><p>Imbalanced datasets can impair the learning performance of many Machine Learning techniques. Nevertheless, many real-world datasets, especially in the healthcare field, are inherently imbalanced. For instance, in the medical domain, the classes representing a specific disease are typically the minority of the total cases. This challenge justifies the substantial research effort spent in the past decades to tackle data imbalance at the data and algorithm levels. In this paper, we describe the strategies we used to deal with an imbalanced classification task on data extracted from a database generated from the Electronic Health Records of the Mental Health Service of the Ferrara Province, Italy. In particular, we applied balancing techniques to the original data, such as random undersampling and oversampling, and Synthetic Minority Oversampling Technique for Nominal and Continuous (SMOTE-NC). In order to assess the effectiveness of the balancing techniques on the classification task at hand, we applied different Machine Learning algorithms. We employed cost-sensitive learning as well and compared its results with those of the balancing methods. Furthermore, a feature selection analysis was conducted to investigate the relevance of each feature. Results show that balancing can help find the best setting to accomplish classification tasks. Since real-world imbalanced datasets are increasingly becoming the core of scientific research, further studies are needed to improve already existing techniques.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"5 ","pages":"Article 100132"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266699002300040X/pdfft?md5=fca4123f44f99c83994cc13701771f05&pid=1-s2.0-S266699002300040X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139190322","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":"Sentiment visualization of correlation of loneliness mapped through social intelligence analysis","authors":"Hurmat Ali Shah,&nbsp;Marco Agus,&nbsp;Mowafa Househ","doi":"10.1016/j.cmpbup.2024.100144","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2024.100144","url":null,"abstract":"<div><h3>Background</h3><p>Loneliness is a global public health issue affecting a considerable number of people as well as burdening the public health system and increasing the risk of other life-threatening and life-damaging conditions. In USA an estimated 17% adults aged 18–70 report loneliness. The monetary loss as result of loneliness is estimated to be between USD 8074.80 and USD 12,0777.70 per person per year in the United Kingdom. But the dynamics of loneliness are not understood. <em>S</em>ocial media platforms have become a valuable source of data to study this phenomenon.</p></div><div><h3>Objectives</h3><p>This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. By using natural language (NLP) processing, sentiment analysis, and topic modeling, we seek to understand prevalent sentiments and concerns. Through interactive tree maps and radar plots, we present an engaging view of loneliness dimensions, allowing users to explore and gain insights into this issue on social media. We focus on comparative analysis of USA and India through analyzing tweets from both countries on loneliness. These two countries are the biggest countries population-wise where access to Twitter is legally allowed.</p></div><div><h3>Methods</h3><p>This study consists of two parts. In the first part, we employ NLP techniques and machine learning algorithms to extract and analyze tweets containing keywords related to loneliness. Through sentiment analysis and topic modeling, we discern linguistic patterns and contextual information to categorize the recurring themes and topics. Advanced text analytics is used to gain nuanced insights into the experiences, emotions, and challenges connected with loneliness. In the second part, interactive visualizations are developed to present the findings in an engaging and intuitive manner. Techniques such as tree maps and radar plots are utilized to transform the analyzed data into visually appealing representations.</p></div><div><h3>Results</h3><p>The analysis of Twitter data yields valuable knowledge about the prevalence and nature of themes and topics associated with loneliness. The interactive visualizations present a comprehensive view of the sentiments and concerns expressed by Twitter users. These interactive plots provide a holistic view of the distribution of themes and topics associated with loneliness, allowing experts to explore and interact with the data, gaining deeper insights into the complexities surrounding this issue.</p></div><div><h3>Conclusion</h3><p>This paper successfully explores themes and topics related to loneliness on Twitter by employing NLP, sentiment analysis, and topic modeling. The interactive visualizations enhance the accessibility and usability of the findings, providing valuable insights for various stakeholders. The study contributes to a deeper comprehension of loneliness in the context of social media.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"5 ","pages":"Article 100144"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666990024000119/pdfft?md5=ad8d535a84d4bca27801d32d83601be9&pid=1-s2.0-S2666990024000119-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140042489","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":"Robust optimization of geometrical properties of flow diverter stents for treating cerebral aneurysm: A proof-of-concept study","authors":"Zahra Darbandi ,&nbsp;Mahkame Sharbatdar ,&nbsp;Mehrdad Raisee","doi":"10.1016/j.cmpbup.2024.100167","DOIUrl":"10.1016/j.cmpbup.2024.100167","url":null,"abstract":"<div><div>This study presents a novel approach to optimize the design of flow diverter (FD) stents for cerebral aneurysm (CA) treatment. By addressing sources of uncertainty in cardiovascular simulations, including geometrical and physical properties and boundary conditions, we aim to assess the applicability of robust optimization techniques to the FD design, establishing a foundation for acquiring robust FDs that are capable of operating consistently under various real-world scenarios. Blood flow in a simplified 2-dimensional CA and FD model was simulated through computational fluid dynamics (CFD). A design space exploration method, incorporating Latin hypercube sampling and Kriging surrogate models, was employed to obtain the optimal solution. The objective was to maximize the reduction in velocity and vorticity within the CA sac. This study used non-intrusive polynomial chaos expansion (PCE) to quantify and propagate the input uncertainties through the computational model and compute the statistical moments of velocity and vorticity reductions. To assess the effect of uncertain sources on objective functions, a sensitivity analysis method based on Sobol indices was applied. Robust optimization involved simultaneously optimizing the mean and standard deviation of velocity reduction. Additionally, we accounted for patients’ specific conditions and repeated the robust optimization. The results indicate that blood Hematocrit and inlet velocity are the most impactful uncertain sources in FD optimization. Moreover, the obtained Pareto front shows that in robust designs, FD struts are concentrated in the distal region of the CA neck, while optimal designs have more struts in the proximal region. This study proposes an FD that compromises robustness and optimality with a velocity reduction of 72.31 % and a standard deviation of 0.00343.</div></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"6 ","pages":"Article 100167"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142326994","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":"Mathematical modelling of COVID-19 transmission with optimal control and cost-effectiveness analysis","authors":"Jufren Zakayo Ndendya,&nbsp;Goodluck Mlay,&nbsp;Herieth Rwezaura","doi":"10.1016/j.cmpbup.2024.100155","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2024.100155","url":null,"abstract":"<div><p>The present global health threat is the novel coronavirus disease (COVID-19), caused by a new strain of the SARS-CoV-2 coronavirus. In this study, have employed optimal control theory, aided by Pontryagin’s Maximum Principle, to explore optimal control measures. Specifically, we have investigated time-dependent intervention strategies, including the proper use of personal protective measures and vaccination. Bifurcation analysis was conducted and results shows that the model system exhibit a forward bifurcation. The optimal control system have been numerically simulated using the fourth-order Runge–Kutta methods. The results show that the implementation of the combination of the two interventions was more significant and effective in minimizing the spread of the COVID-19 than the implementation of a single control measure. These findings underscore the significance of multifaceted intervention approaches over singular control measures. Notably, the combined implementation of interventions emerges as markedly more effective in containing COVID-19 transmission. Moreover, our study identifies personal protective measures as a particularly cost-effective intervention, offering substantial relief from the burden of the pandemic within the population. We anticipate that our research will inform evidence-based approaches to pandemic control and aid in the ongoing global efforts to safeguard public health.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"5 ","pages":"Article 100155"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666990024000223/pdfft?md5=9a97650d33c27c586931ccfb4171acc7&pid=1-s2.0-S2666990024000223-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140650571","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":"Fuzzy information granulation towards benign and malignant lung nodules classification","authors":"Fatemeh Amini ,&nbsp;Roya Amjadifard ,&nbsp;Azadeh Mansouri","doi":"10.1016/j.cmpbup.2024.100153","DOIUrl":"https://doi.org/10.1016/j.cmpbup.2024.100153","url":null,"abstract":"<div><p>Lung cancer is the second common cancer with the highest death rate in the world. Cancer diagnosis in the early stages is a critical factor for increasing the treatment speed. This paper proposes a new machine learning method based on a fuzzy approach to detect benign and malignant lung nodules to early-diagnose lung cancer by investigating the computed tomography (CT) images. First, the lung nodule images are pre-processed via the Gabor wavelet transform. Then, some of the texture features are extracted from the transformed domain based on the statistical characteristics and histogram of the local patterns of images. Finally, based on the fuzzy information granulation (FIG) method, which is widely recognized as being able to distinguish between similar textures, a FIG-based classifier is introduced to classify the benign and malignant lung nodules. The clinical data set used for this research are a combination of 150 CT scans of LIDC and SPIE-APPM data sets. Also the LIDC data set is analyzed alone. The results show that the proposed method can be an innovative alternative to classify the benign and malignant nodules in the CT images.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"5 ","pages":"Article 100153"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266699002400020X/pdfft?md5=d43ed81b678b0d363064540232814404&pid=1-s2.0-S266699002400020X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140548499","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":"Irreversible electroporation for tissue ablation: A 3D computational platform","authors":"Sudip Kumar Das ,&nbsp;Srinivasan Jayaraman","doi":"10.1016/j.cmpbup.2024.100163","DOIUrl":"10.1016/j.cmpbup.2024.100163","url":null,"abstract":"<div><h3>Background and objective:</h3><p>Globally, irreversible electroporation (IRE) emerges as a promising technique for tissue ablation as it overcomes the limitations of the benchmark techniques. However, achieving the desired and safe ablation volume of tissue pivots on multiple factors, such as pulse profile, shape, and number of electrodes, besides the IRE treatment parameters, like pulse type, field strength, number of pulses, pulse length, and frequency. This work aims to develop a <span><math><mi>3D</mi></math></span> computation platform that predicts the ablation volume using the IRE procedure and provides insights such as electric field, temperature and its corresponding cell survival regions. Thereby, such a platform aids in selecting optimized treatment parameters to avoid thermal damage. In addition, the developed IRE model estimates the relationship between the pulse protocol and different electrode geometries, number of electrodes, and electrode configurations.</p></div><div><h3>Methods:</h3><p>The computational model for IRE is developed with Laplace’s equation and Penn’s bio-heat equation for the electric potential and temperature profiles, respectively, and the Finite Difference method is considered for the numerical solution. The statistical Fermi equation-based Peleg model has been adapted to estimate the ablation volume as a function of the magnitude of the electric field and other electric field parameters.</p></div><div><h3>Results:</h3><p>The tissue ablation platform allows computation and visualization of ablation volume estimation using the IRE technique with a pair of plate-type and multiple pairs of needle-type electrodes. IRE treatment with different combinations of electric pulse parameters, i.e., pulse length, voltage, and number of pulses, causes different levels of temperature rise. By adapting our platform, one can avoid thermal damage in the IRE treatment with the right combination of pulse parameters. For instance, one can apply a maximum of 10 pulses restricting temperature within <span><math><mrow><mn>50</mn><mspace></mspace><mo>°</mo><mi>C</mi></mrow></math></span> in the IRE treatment of cervical tissue with a couple of pairs of needle-type electrodes and <span><math><mrow><mn>100</mn><mspace></mspace><mi>μ</mi><mi>s</mi></mrow></math></span> electric pulses of <span><math><mrow><mn>3000</mn><mspace></mspace><mi>V</mi></mrow></math></span>.</p></div><div><h3>Conclusion:</h3><p>The proposed IRE model aids in treatment planning for tissue ablation with <span><math><mi>3D</mi></math></span> visual outputs through the platform’s user interface for better clinical insights, including interpretability, data resolution, and computational cost.</p></div>","PeriodicalId":72670,"journal":{"name":"Computer methods and programs in biomedicine update","volume":"6 ","pages":"Article 100163"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666990024000302/pdfft?md5=95221513af1d6ad772e3f8f50c180369&pid=1-s2.0-S2666990024000302-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232494","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}