{"results":[{"id":"ss_3d4c709be74c6926b220f4cf7d8adf50082f3886","title":"Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)","authors":[{"name":"F. Amirabdollahian"},{"name":"K. Dautenhahn"},{"name":"C. Dixon"},{"name":"K. Eder"},{"name":"Michael Fisher"},{"name":"K. Koay"},{"name":"E. Magid"},{"name":"Tony Pipe"},{"name":"Maha Salem"},{"name":"J. Saunders"},{"name":"M. Webster"}],"abstract":"","source":"Semantic Scholar","year":2013,"language":"en","subjects":["Computer Science"],"url":"https://www.semanticscholar.org/paper/3d4c709be74c6926b220f4cf7d8adf50082f3886","is_open_access":true,"citations":1787,"published_at":"","score":87},{"id":"ss_9679554de5f828ea4506fedb5921d67a16a8e618","title":"An introduction to computer science for non-majors using principles of computation","authors":[{"name":"Thomas J. Cortina"}],"abstract":"","source":"Semantic Scholar","year":2007,"language":"en","subjects":["Computer Science"],"doi":"10.1145/1227310.1227387","url":"https://www.semanticscholar.org/paper/9679554de5f828ea4506fedb5921d67a16a8e618","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=1227387\u0026type=pdf","is_open_access":true,"citations":2853,"published_at":"","score":81},{"id":"ss_21f389aabe2491d620ce920e3bad2b12521fa025","title":"Algorithms on Strings, Trees, and Sequences - Computer Science and Computational Biology","authors":[{"name":"D. Gusfield"}],"abstract":"","source":"Semantic Scholar","year":1997,"language":"en","subjects":["Computer Science"],"doi":"10.1017/cbo9780511574931","url":"https://www.semanticscholar.org/paper/21f389aabe2491d620ce920e3bad2b12521fa025","is_open_access":true,"citations":4580,"published_at":"","score":80},{"id":"ss_cf9ecfbbd0095687c4cfbbbfa0546914e651b109","title":"Calibration of the Computer Science and Applications, Inc. accelerometer.","authors":[{"name":"P. Freedson"},{"name":"E. Melanson"},{"name":"J. Sirard"}],"abstract":"","source":"Semantic Scholar","year":1998,"language":"en","subjects":["Computer Science","Medicine"],"doi":"10.1097/00005768-199805000-00021","url":"https://www.semanticscholar.org/paper/cf9ecfbbd0095687c4cfbbbfa0546914e651b109","pdf_url":"https://doi.org/10.1097/00005768-199805000-00021","is_open_access":true,"citations":3749,"published_at":"","score":80},{"id":"ss_86b05bc7e953e683fa839ad01d6100a8f99558df","title":"Concrete mathematics - a foundation for computer science","authors":[{"name":"R. Graham"},{"name":"D. Knuth"},{"name":"Or Patashnik"}],"abstract":"","source":"Semantic Scholar","year":1991,"language":"en","subjects":["Computer Science","Mathematics"],"doi":"10.2307/2324448","url":"https://www.semanticscholar.org/paper/86b05bc7e953e683fa839ad01d6100a8f99558df","pdf_url":"http://www.gbv.de/dms/ilmenau/toc/513752366graha.PDF","is_open_access":true,"citations":3045,"published_at":"","score":80},{"id":"ss_05913f4b504aa1fb1e638cdd0848d94bf5eb43da","title":"Probability and Statistics with Reliability, Queuing, and Computer Science Applications","authors":[{"name":"Kishor S. Trivedi"}],"abstract":"","source":"Semantic Scholar","year":1984,"language":"en","subjects":["Computer Science"],"doi":"10.2307/2322693","url":"https://www.semanticscholar.org/paper/05913f4b504aa1fb1e638cdd0848d94bf5eb43da","is_open_access":true,"citations":2941,"published_at":"","score":80},{"id":"ss_b15c4a76dd6c8d9cfe457635a998405605592244","title":"How-to conduct a systematic literature review: A quick guide for computer science research","authors":[{"name":"Angela Carrera-Rivera"},{"name":"William Ochoa-Agurto"},{"name":"F. Larrinaga"},{"name":"Ganix Lasa"}],"abstract":"Performing a literature review is a critical first step in research to understanding the state-of-the-art and identifying gaps and challenges in the field. A systematic literature review is a method which sets out a series of steps to methodically organize the review. In this paper, we present a guide designed for researchers and in particular early-stage researchers in the computer-science field. The contribution of the article is the following:• Clearly defined strategies to follow for a systematic literature review in computer science research, and• Algorithmic method to tackle a systematic literature review.","source":"Semantic Scholar","year":2022,"language":"en","subjects":["Medicine"],"doi":"10.1016/j.mex.2022.101895","url":"https://www.semanticscholar.org/paper/b15c4a76dd6c8d9cfe457635a998405605592244","pdf_url":"http://ebiltegia.mondragon.edu/xmlui/bitstream/20.500.11984/5902/1/How-to%20conduct%20a%20systematic%20literature%20review%20A%20quick%20guide%20for%20computer%20science%20research.pdf","is_open_access":true,"citations":390,"published_at":"","score":77.7},{"id":"ss_0394864f253fd69284462664d5725ad6ba7aa6e1","title":"Teaching CS50 with AI: Leveraging Generative Artificial Intelligence in Computer Science Education","authors":[{"name":"Rong Liu"},{"name":"Carter Zenke"},{"name":"Charlie Liu"},{"name":"A. Holmes"},{"name":"Patrick Thornton"},{"name":"David J. Malan"}],"abstract":"In Summer 2023, we developed and integrated a suite of AI-based software tools into CS50 at Harvard University. These tools were initially available to approximately 70 summer students, then to thousands of students online, and finally to several hundred on campus during Fall 2023. Per the course's own policy, we encouraged students to use these course-specific tools and limited the use of commercial AI software such as ChatGPT, GitHub Copilot, and the new Bing. Our goal was to approximate a 1:1 teacher-to-student ratio through software, thereby equipping students with a pedagogically-minded subject-matter expert by their side at all times, designed to guide students toward solutions rather than offer them outright. The tools were received positively by students, who noted that they felt like they had \"a personal tutor.'' Our findings suggest that integrating AI thoughtfully into educational settings enhances the learning experience by providing continuous, customized support and enabling human educators to address more complex pedagogical issues. In this paper, we detail how AI tools have augmented teaching and learning in CS50, specifically in explaining code snippets, improving code style, and accurately responding to curricular and administrative queries on the course's discussion forum. Additionally, we present our methodological approach, implementation details, and guidance for those considering using these tools or AI generally in education.","source":"Semantic Scholar","year":2024,"language":"en","subjects":["Computer Science"],"doi":"10.1145/3626252.3630938","url":"https://www.semanticscholar.org/paper/0394864f253fd69284462664d5725ad6ba7aa6e1","is_open_access":true,"citations":187,"published_at":"","score":73.61},{"id":"ss_76fd6b211334b7dc486ad475fe897982134a0d93","title":"Gender stereotypes about interests start early and cause gender disparities in computer science and engineering","authors":[{"name":"Allison Master"},{"name":"A. Meltzoff"},{"name":"S. Cheryan"}],"abstract":"Significance Societal stereotypes that girls are less interested than boys in computer science and engineering are endorsed by children and adolescents in a large and socioeconomically diverse sample, across multiple racial/ethnic and gender intersections, and as early as age six (first grade). Gender-interest stereotypes may contribute to subsequent gender disparities in the pursuit of these societally important fields. Addressing interest stereotypes may help improve educational equity. Societal stereotypes depict girls as less interested than boys in computer science and engineering. We demonstrate the existence of these stereotypes among children and adolescents from first to 12th grade and their potential negative consequences for girls’ subsequent participation in these fields. Studies 1 and 2 (n = 2,277; one preregistered) reveal that children as young as age six (first grade) and adolescents across multiple racial/ethnic and gender intersections (Black, Latinx, Asian, and White girls and boys) endorse stereotypes that girls are less interested than boys in computer science and engineering. The more that individual girls endorse gender-interest stereotypes favoring boys in computer science and engineering, the lower their own interest and sense of belonging in these fields. These gender-interest stereotypes are endorsed even more strongly than gender stereotypes about computer science and engineering abilities. Studies 3 and 4 (n = 172; both preregistered) experimentally demonstrate that 8- to 9-y-old girls are significantly less interested in an activity marked with a gender stereotype (“girls are less interested in this activity than boys”) compared to an activity with no such stereotype (“girls and boys are equally interested in this activity”). Taken together, both ecologically valid real-world studies (Studies 1 and 2) and controlled preregistered laboratory experiments (Studies 3 and 4) reveal that stereotypes that girls are less interested than boys in computer science and engineering emerge early and may contribute to gender disparities.","source":"Semantic Scholar","year":2021,"language":"en","subjects":["Medicine"],"doi":"10.1073/pnas.2100030118","url":"https://www.semanticscholar.org/paper/76fd6b211334b7dc486ad475fe897982134a0d93","pdf_url":"https://doi.org/10.1073/pnas.2100030118","is_open_access":true,"citations":237,"published_at":"","score":72.11},{"id":"ss_94f1d3d29ee1639db4fd5500d9c60807dd79cf22","title":"Multiobjective Optimization Interactive And Evolutionary Approaches Lecture Notes In Computer Science Theoretical Computer Science And General Issues","authors":null,"abstract":"","source":"Semantic Scholar","year":2022,"language":"en","subjects":null,"url":"https://www.semanticscholar.org/paper/94f1d3d29ee1639db4fd5500d9c60807dd79cf22","is_open_access":true,"citations":181,"published_at":"","score":71.43},{"id":"ss_3b292cc8b71a0daadd90fa35792f7ce42799cb8d","title":"Computer Science Curricula 2023","authors":[{"name":"Amruth N. Kumar"},{"name":"R. Raj"},{"name":"S. Aly"},{"name":"Monica D. Anderson"},{"name":"Brett A. Becker"},{"name":"Richard Blumenthal"},{"name":"Eric Eaton"},{"name":"Susan L. Epstein"},{"name":"Michael Goldweber"},{"name":"Pankaj Jalote"},{"name":"Doug Lea"},{"name":"Michael Oudshoorn"},{"name":"Marcelo Pias"},{"name":"Susan L. Reiser"},{"name":"Christian Servin"},{"name":"Rahul Simha"},{"name":"Titus Winters"},{"name":"Qiao Xiang"}],"abstract":"","source":"Semantic Scholar","year":2024,"language":"en","subjects":null,"doi":"10.1145/3664191","url":"https://www.semanticscholar.org/paper/3b292cc8b71a0daadd90fa35792f7ce42799cb8d","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3664191","is_open_access":true,"citations":108,"published_at":"","score":71.24000000000001},{"id":"ss_19a12f85bacfaeb374582408a9aa844c29b52dbe","title":"Game-based learning in computer science education: a scoping literature review","authors":[{"name":"Maja Videnovik"},{"name":"T. Vold"},{"name":"L. Kiønig"},{"name":"Ana Madevska Bogdanova"},{"name":"V. Trajkovik"}],"abstract":"Using games in education has the potential to increase students’ motivation and engagement in the learning process, gathering long-lasting practical knowledge. Expanding interest in implementing a game-based approach in computer science education highlights the need for a comprehensive overview of the literature research. This scoping review aims to provide insight into current trends and identify research gaps and potential research topics concerning game-based learning in computer science. Using standard methodology for scoping review, we identified 113 articles from four digital libraries published between 2017 and 2021. Those articles were analyzed concerning the educational level, type of the game, computer science topic covered by the game, pedagogical strategies, and purpose for implementing this approach in different educational levels. The results show that the number of research articles has increased through the years, confirming the importance of implementing a game-based approach in computer science. Different kinds of games, using different technology, concerning different computer science topics are presented in the research. The obtained results indicate that there is no standardized game or standardized methodology that can be used for the creation of an educational game for computer science education. Analyzed articles mainly implement a game-based approach using learning by playing, and no significant focus is given to the effectiveness of learning by designing a game as a pedagogical strategy. Moreover, the approach is mainly implemented for developing computational thinking or programming skills, highlighting the need for its implementation in other topics beyond programming.","source":"Semantic Scholar","year":2023,"language":"en","subjects":null,"doi":"10.1186/s40594-023-00447-2","url":"https://www.semanticscholar.org/paper/19a12f85bacfaeb374582408a9aa844c29b52dbe","pdf_url":"https://stemeducationjournal.springeropen.com/counter/pdf/10.1186/s40594-023-00447-2","is_open_access":true,"citations":97,"published_at":"","score":69.91},{"id":"doaj_10.1002/eng2.13035","title":"Path Planning Approaches in Multi‐robot System: A Review","authors":[{"name":"Semonti Banik"},{"name":"Sajal Chandra Banik"},{"name":"Sarker Safat Mahmud"}],"abstract":"ABSTRACT The essential factor in developing multi‐robot systems is the generation of an optimal path for task completion by multiple robots. To ensure effective path planning, this paper studies the recent publications and provides a detailed review of the path planning approaches to avoid collisions in uncertain environments. In this article, path‐planning approaches for multiple robots are categorized primarily into classical, heuristic, and artificial intelligence‐based methods. Among the heuristic approaches, bio‐inspired approaches are mostly employed to optimize the classical approaches to enhance their adaptability. The articles are analyzed based on static and dynamic scenarios, real‐time experiments, and simulations involving hybrid solutions. The increasing focus on using hybrid approaches in dynamic environments is found mostly in the papers employing heuristic and AI‐based approaches. In real‐time applications, AI‐based approaches are highly implemented in comparison to heuristic and classical approaches. Moreover, the findings from this review, highlighting the strengths and drawbacks of each algorithm, can help researchers select the appropriate approach to overcome the limitations in designing efficient multi‐robot systems.","source":"DOAJ","year":2025,"language":"","subjects":["Engineering (General). Civil engineering (General)","Electronic computers. Computer science"],"doi":"10.1002/eng2.13035","url":"https://doi.org/10.1002/eng2.13035","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.46481/jnsps.2025.2273","title":"A feature selection and scoring scheme for dimensionality reduction in a machine learning task","authors":[{"name":"PHILEMON UTEN EMMOH"},{"name":"christopher  ifeanyi Eke"},{"name":"Timothy Moses"}],"abstract":"\nSelection of important features is very vital in machine learning tasks involving high-dimensional dataset with large features. It helps in reducing the dimensionality of a dataset and improving model performance. Most of the feature selection techniques have restriction in the kind of dataset to be used. This study proposed a feature selection technique that is based on statistical lift measure to select important features from a dataset. The proposed technique is a generic approach that can be used in any binary classification dataset. The technique successfully determined the most important feature subset and outperformed the existing techniques. The proposed technique was tested on lungs cancer dataset and happiness classification dataset. The effectiveness of the proposed technique in selecting important features subset was evaluated and compared with other existing techniques, namely Chi-Square, Pearson Correlation and Information Gain. Both the proposed and the existing techniques were evaluated on five machine learning models using four standard evaluation metrics such as accuracy, precision, recall and F1-score. The experimental results of the proposed technique on lung cancer dataset shows that logistic regression, decision tree, adaboost, gradient boost and random forest produced a predictive accuracy of 0.919%, 0.935%, 0.919%, 0.935% and 0.935% respectively, and that of happiness classification dataset produced a predictive accuracy of 0.758%, 0.689%, 0.724%, 0.655% and 0.689% on random forest, k-nearest neighbor, decision tree, gradient boost and cat boost respectively, which outperformed the existing techniques.\n","source":"DOAJ","year":2025,"language":"","subjects":["Physics"],"doi":"10.46481/jnsps.2025.2273","url":"https://journal.nsps.org.ng/index.php/jnsps/article/view/2273","is_open_access":true,"published_at":"","score":69},{"id":"doaj_10.1016/j.eng.2024.10.021","title":"LearningEMS: A Unified Framework and Open-Source Benchmark for Learning-Based Energy Management of Electric Vehicles","authors":[{"name":"Yong Wang"},{"name":"Hongwen He"},{"name":"Yuankai Wu"},{"name":"Pei Wang"},{"name":"Haoyu Wang"},{"name":"Renzong Lian"},{"name":"Jingda Wu"},{"name":"Qin Li"},{"name":"Xiangfei Meng"},{"name":"Yingjuan Tang"},{"name":"Fengchun Sun"},{"name":"Amir Khajepour"}],"abstract":"An effective energy management strategy (EMS) is essential to optimize the energy efficiency of electric vehicles (EVs). With the advent of advanced machine learning techniques, the focus on developing sophisticated EMS for EVs is increasing. Here, we introduce LearningEMS: a unified framework and open-source benchmark designed to facilitate rapid development and assessment of EMS. LearningEMS is distinguished by its ability to support a variety of EV configurations, including hybrid EVs, fuel cell EVs, and plug-in EVs, offering a general platform for the development of EMS. The framework enables detailed comparisons of several EMS algorithms, encompassing imitation learning, deep reinforcement learning (RL), offline RL, model predictive control, and dynamic programming. We rigorously evaluated these algorithms across multiple perspectives: energy efficiency, consistency, adaptability, and practicability. Furthermore, we discuss state, reward, and action settings for RL in EV energy management, introduce a policy extraction and reconstruction method for learning-based EMS deployment, and conduct hardware-in-the-loop experiments. In summary, we offer a unified and comprehensive framework that comes with three distinct EV platforms, over 10  000 km of EMS policy data set, ten state-of-the-art algorithms, and over 160 benchmark tasks, along with three learning libraries. Its flexible design allows easy expansion for additional tasks and applications. The open-source algorithms, models, data sets, and deployment processes foster additional research and innovation in EV and broader engineering domains.","source":"DOAJ","year":2025,"language":"","subjects":["Engineering (General). Civil engineering (General)"],"doi":"10.1016/j.eng.2024.10.021","url":"http://www.sciencedirect.com/science/article/pii/S2095809924007136","is_open_access":true,"published_at":"","score":69},{"id":"arxiv_2512.16152","title":"Pulsar Science with the SKA Observatory","authors":[{"name":"Bhal Chandra Joshi"},{"name":"Aris Karastergiou"},{"name":"Marta Burgay"},{"name":"The SKA pulsar science working group"}],"abstract":"The large instantaneous sensitivity, a wide frequency coverage and flexible observation modes with large number of beams in the sky are the main features of the SKA observatory's two telescopes, the SKA-Low and the SKA-Mid, which are located on two different continents. Owing to these capabilities, the SKAO telescopes are going to be a game-changer for radio astronomy in general and pulsar astronomy in particular. The eleven articles in this special issue on pulsar science with the SKA Observatory describe its impact on different areas of pulsar science. In this lead article, a brief description of the two telescopes highlighting the relevant features for pulsar science is presented followed by an overview of each accompanying article, exploring the inter-relationship between different pulsar science use cases.","source":"arXiv","year":2025,"language":"en","subjects":["astro-ph.HE","astro-ph.IM"],"url":"https://arxiv.org/abs/2512.16152","pdf_url":"https://arxiv.org/pdf/2512.16152","is_open_access":true,"published_at":"2025-12-18T04:16:35Z","score":69},{"id":"arxiv_2507.11543","title":"A Review of Generative AI in Computer Science Education: Challenges and Opportunities in Accuracy, Authenticity, and Assessment","authors":[{"name":"Iman Reihanian"},{"name":"Yunfei Hou"},{"name":"Yu Chen"},{"name":"Yifei Zheng"}],"abstract":"This paper surveys the use of Generative AI tools, such as ChatGPT and Claude, in computer science education, focusing on key aspects of accuracy, authenticity, and assessment. Through a literature review, we highlight both the challenges and opportunities these AI tools present. While Generative AI improves efficiency and supports creative student work, it raises concerns such as AI hallucinations, error propagation, bias, and blurred lines between AI-assisted and student-authored content. Human oversight is crucial for addressing these concerns. Existing literature recommends adopting hybrid assessment models that combine AI with human evaluation, developing bias detection frameworks, and promoting AI literacy for both students and educators. Our findings suggest that the successful integration of AI requires a balanced approach, considering ethical, pedagogical, and technical factors. Future research may explore enhancing AI accuracy, preserving academic integrity, and developing adaptive models that balance creativity with precision.","source":"arXiv","year":2025,"language":"en","subjects":["cs.CY","cs.AI"],"url":"https://arxiv.org/abs/2507.11543","pdf_url":"https://arxiv.org/pdf/2507.11543","is_open_access":true,"published_at":"2025-06-17T19:20:58Z","score":69},{"id":"ss_04a08302c471705809f6cb5ae6a88451f9df98a5","title":"Coding as another language: a pedagogical approach for teaching computer science in early childhood","authors":[{"name":"M. Bers"}],"abstract":"","source":"Semantic Scholar","year":2019,"language":"en","subjects":["Computer Science","Mathematics","Psychology"],"doi":"10.1007/s40692-019-00147-3","url":"https://www.semanticscholar.org/paper/04a08302c471705809f6cb5ae6a88451f9df98a5","is_open_access":true,"citations":191,"published_at":"","score":68.73},{"id":"ss_45c5605ea67978dec4b10ad462fd32c7f986828f","title":"Threats of a replication crisis in empirical computer science","authors":[{"name":"A. Cockburn"},{"name":"Pierre Dragicevic"},{"name":"L. Besançon"},{"name":"C. Gutwin"}],"abstract":"Research replication only works if there is confidence built into the results.","source":"Semantic Scholar","year":2020,"language":"en","subjects":["Computer Science"],"doi":"10.1145/3360311","url":"https://www.semanticscholar.org/paper/45c5605ea67978dec4b10ad462fd32c7f986828f","pdf_url":"https://liu.diva-portal.org/smash/get/diva2:1502227/FULLTEXT01","is_open_access":true,"citations":149,"published_at":"","score":68.47},{"id":"doaj_10.1177/09636897241253144","title":"ITRI Biofilm Prevented Thoracic Adhesion in Pigs That Received Myocardial Ischemic Induction Treated by Myocardial Implantation of EPCs and ECSW Treatment","authors":[{"name":"Jiunn-Jye Sheu"},{"name":"Jui-Ning Yeh"},{"name":"Pei-Hsun Sung"},{"name":"John Y. Chiang"},{"name":"Yi-Ling Chen"},{"name":"Yi-Ting Wang"},{"name":"Hon-Kan Yip"},{"name":"Jun Guo"}],"abstract":"This study tested the hypothesis that ITRI Biofilm prevents adhesion of the chest cavity. Combined extracorporeal shock wave (ECSW) + bone marrow-derived autologous endothelial progenitor cell (EPC) therapy was superior to monotherapy for improving heart function (left ventricular ejection fraction [LVEF]) in minipigs with ischemic cardiomyopathy (IC) induced by an ameroid constrictor applied to the mid-left anterior descending artery. The minipigs ( n = 30) were equally designed into group 1 (sham-operated control), group 2 (IC), group 3 (IC + EPCs/by directly implanted into the left ventricular [LV] myocardium; 3 [+]/3[–] ITRI Biofilm), group 4 (IC + ECSW; 3 [+]/[3] – ITRI Biofilm), and group 5 (IC + EPCs–ECSW; 3 [+]/[3] – ITRI Biofilm). EPC/ECSW therapy was administered by day 90, and the animals were euthanized, followed by heart harvesting by day 180. In vitro studies demonstrated that cell viability/angiogenesis/cell migratory abilities/mitochondrial concentrations were upregulated in EPCs treated with ECSW compared with those in EPCs only (all P s \u003c 0.001). The LVEF was highest in group 1/lowest in group 2/significantly higher in group 5 than in groups 3/4 (all P s \u003c 0.0001) by day 180, but there was no difference in groups 3/4. The adhesion score was remarkably lower in patients who received ITRI Biofilm treatment than in those who did not (all P s \u003c0.01). The protein expressions of oxidative stress (NOX-1/NOX-2/oxidized protein)/apoptotic (mitochondrial-Bax/caspase3/PARP)/fibrotic (TGF-β/Smad3)/DNA/mitochondria-damaged (γ-H2AX/cytosolic-cytochrome-C/p-DRP1), and heart failure/pressure-overload (BNP [brain natriuretic peptide]/β-MHC [beta myosin heavy chain]) biomarkers displayed a contradictory manner of LVEF among the groups (all P s \u003c 0.0001). The protein expression of endothelial biomarkers (CD31/vWF)/small-vessel density revealed a similar LVEF within the groups (all P s \u003c 0.0001). ITRI Biofilm treatment prevented chest cavity adhesion and was superior in restoring IC-related LV dysfunction when combined with EPC/ECSW therapy compared with EPC/ECSW therapy alone.","source":"DOAJ","year":2024,"language":"","subjects":["Medicine"],"doi":"10.1177/09636897241253144","url":"https://doi.org/10.1177/09636897241253144","is_open_access":true,"published_at":"","score":68}],"total":22561520,"page":1,"page_size":20,"sources":["CrossRef","DOAJ","Semantic Scholar","arXiv"],"query":"Computer Science"}