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关键词： Health sciences   Natural sciences   Computer science  

摘要： Lumbar disc herniation (LDH) is a common cause of lower back pain and sciatica, and posterior lumbar interbody fusion (PLIF) is always employed. This multicenter retrospective study investigates predicting intraoperative blood transfusion for LDH patients undergoing PLIF in China. The research includes 6,241 patients from 22 medical centers and employs 8 feature selection methods and 10 machine learning models, including an integrated stacking model. The optimal predictive model was selected based on the receiver operating characteristic area under the curve, clinical applicability, and computational efficiency. Among the evaluated combinations, the simulated annealing support vector machine recursive + stacking model achieved the highest performance with an area under the curve of 0.884, supported by robust calibration and decision curve analyses. A publicly accessible web calculator was developed to assist clinicians in decision-making. This work significantly enhances intraoperative transfusion predictions, providing valuable tools for improving patient management.

关键词： Health informatics   Computer science   Machine learning  

摘要： Difference-in-differences (DID) is a key tool for causal impact evaluation but faces challenges when applied to sensitive data restricted by privacy regulations. Obtaining consent can shrink sample sizes and reduce statistical power, limiting the analysis's effectiveness. Federated learning addresses these issues by sharing aggregated statistics rather than individual data, though advanced federated DID software is limited. We developed a federated version of the Callaway and Sant'Anna difference-in-differences (CSDID), integrated into the DataSHIELD platform, adhering to stringent privacy protocols. Our approach reproduces key estimates and standard errors while preserving confidentiality. Using simulated and real- world data from a malaria intervention in Mozambique, we demonstrate that federated estimates increase sample sizes, reduce estimation uncertainty, and enable analyses when data owners cannot share treated or untreated group data. Our work contributes to facilitating the evaluation of policy interventions or treatments across centers and borders.

摘要： Jacques Derrida's claim that Immanuel Kant was the most rigorous defender of the death penalty has rekindled interest in this topic in the context of Kant's work. Understandably, most articles have focused on Kant's The Metaphysics of Morals, in which he defends the legitimacy of capital punishment. However, many of these readings ignore the fact that the death penalty is a recurring theme in his writing. This article explores references to capital punishment in Kant's Critique of Practical Reason and uncovers a consistent theme: the connection between morality and acts of self-sacrifice. It aims to demonstrate the challenges of formulating a philosophical argument for the abolition of the death penalty.

关键词： Clustering algorithms   Heuristic algorithms   Encoding   Graph neural networks   Detection algorithms   Clustering methods   Image edge detection   Electronic learning   Computer science   Vectors   Community detection   deep graph clustering   e-learning   user clustering  

摘要： Deep graph clustering is a highly significant tool for community detection, enabling the identification of strongly connected groups of nodes within a graph. This technology is crucial in various fields such as education and E-learning. However, deep graph clustering can be more misled by the graph topology, disregarding node information. For example, an excessive number of intercommunity edges or insufficient intracommunity edges can lead to inaccurate community distinction by the model. In this article, we propose a novel model, deep Graph Clustering with Triple Fusion Autoencoder (GC-TriFA) for community detection, which utilizes a triple encoding fusion mechanism to balance the incorporation of node and topological information, thereby mitigating this issue. Specifically, GC-TriFA employs a shallow linear coding fusion and a deep coding fusion method within an autoencoder structure. This approach enables the model to simultaneously learn and capture the embedding of cross-modality information and later utilizes weight fusion to equalize the two modalities. Furthermore, GC-TriFA also reconstructs the graph structure, learns relaxed $k$-means, and undergoes self-supervised training to enhance the quality of the graph embedding. The experimental results of GC-TriFA, when evaluated as an end-to-end model on publicly available datasets, demonstrate its superiority compared to the baseline models.

关键词： Adversarial machine learning  

摘要： Steve Jobs once said that one of his goals as head of Apple was to "bring a liberal arts perspective... to what had traditionally been a very geeky technology and a very geeky audience"[11]. Jobs, of course, succeeded and made personal computers easy, and even fun, to use. A geeky tool went mainstream, and we all benefitted. Although Jobs and Apple changed computing forever, computer science education at many universities has struggled to overcome the stereotype as a home for geeky students more comfortable communicating through algorithms than through speech. Changing that stereotype and creating computer science education that speaks to the needs of today's society is a challenge for those who work to educate future computer scientists. When it comes to academic disciplines, computer science is still a youngster, first appearing at the university level in the 1950s and 1960s and continuing to evolve and expand through the age of personal computing, the internet and the cloud, the creation of massively parallel machines, and the rise of the interconnected Internet of Things, machine learning (ML) and artificial intelligence (AI). © 2024 Copyright held by owner/author(s). Publication rights licensed to ACM.

关键词： Cost engineering  

摘要： This piece points out the key position of formal methods in Computer Science (CS) education, which must thus be reflected in any CS curriculum as a knowledge area rather than as elective topics in distinct knowledge areas. This is confirmed by the increasing use of formal methods in industry [4]-not limited to safety-critical domains. First, we indicate the importance of formal methods thinking in CS education [17], since this provides the necessary rigor in reasoning about software, its specification, its verification, and its correctness-all fundamental skills for future software developers. Then, we argue that every computer scientist needs to know formal methods [6], since the skills and knowledge acquired in this way provide the indispensable solid foundation that forms the backbone of CS practice. Finally, we underline that teaching formal methods need not come at the cost of displacing other engineering aspects of CS that are already widely accepted as essential. On the contrary, formal methods have the potential to support and strengthen the presentation and knowledge in all these subdisciplines. We provide suggestions for educators on how to incorporate formal methods into CS education. © 2024 Copyright held by owner/author(s).

关键词： Computer science   artificial intelligence  

ISBN: (数字)9781394214259 ISBN: (纸本)9781394214228

摘要： This book provides a comprehensive exploration of computational intelligence techniques and their applications, offering valuable insights into advanced information processing, machine learning concepts, and their impact on agile manufacturing systems. Computational Intelligence presents a new concept for advanced information processing.

关键词： Climate change   Computer science   Government   Health care   Policy   Politics  

摘要： Donald Trump made numerous promises during his presidential campaign that could affect scientists and science policy. Will they be implemented once he is president?

关键词： Students  

摘要： Upon release, ChatGPT3.5 shocked the software engineering community by its ability to generate answers to specialized questions about coding. Immediately, many educators wondered if it was possible to use the chatbot as a support tool that helps students answer their programming questions. This article evaluates this possibility at three levels: fundamental Computer Science knowledge (basic algorithms and data structures), core competency (design patterns), and advanced knowledge (quantum computing). In each case, we ask normalized questions several times to ChatGPT3.5, then look at the correctness of answers, and finally check if this creates issues. The main result is that the performances of ChatGPT3.5 degrades drastically as the specialization of the domain increases: for basic algorithms it returns answers that are almost always correct, for design patterns the generated code contains many code smells and is generally of low quality, but it is still sometimes able to fix it (if asked), and for quantum computing it is often blatantly wrong. © 2024, CC BY-NC-ND.

关键词： Computer science   Conferences and meetings   Machine learning   Publishing  

摘要： At major computer-science publication venues, up to 17% of the peer reviews are now written by artificial intelligence. We need guidelines before things get out of hand.