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Combining machine learning models and rule engines in clinical decision systems: Exploring optimal aggregation methods for vaccine hesitancy prediction

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computers in Biology and Medicine 2025年 188卷 109749-109749页

作者： Kierner, Slawomir Kierner, Piotr Kucharski, Jacek Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Genetics – Blavatnik Institute Sinclair Lab Harvard Medical School D 77 Avenue Louis Pasteur BostonMA02115 United States Faculty of Electrical Electronic Computer and Control Engineering Lodz University of Technology 18/22 Stefanowskiego St. Lodź90-924 Poland

Background: With the increasing application of artificial intelligence (AI) technologies in the healthcare sector and the emergence of new solutions, such as large language models, there is a growing need to combine medical knowledge, often expressed as clinical rules, with advances in machine learning (ML) offering higher prediction accuracy at the expense of decision-making transparency. Purpose: This study investigates the efficacy of various aggregation methods combining the decisions of an AI model and a clinical rule-based (RB) engine in predicting vaccine hesitancy to maximize the effectiveness of patient incentive programs. This is the first study of parallel ensemble of rules and machine learning in clinical context proposing RB confidence-led fusion of ML and RB inference. Methods: A clinical decision system for predicting hesitation to vaccinate is developed based on a differentially private set of longitudinal health records of 974,000 US patients and clinical rules obtained from the present literature. Various approaches based on possibility theory have been explored to maximize classification accuracy, capture and hurdle rates while ensuring trustworthiness in clinical interventions. Results: Our findings reveal that the hybrid approach outperforms the individual models and RB systems when transparency and accuracy are critical. A RB confidence-led approach emerged as the most effective method. The aggregation of mismatched classes relies on RB results when the RB engine has high confidence (expressed as more than the median degree of membership to the vaccination hesitation output function) and on ML predictions when the RB engine exhibits lower confidence. Conclusions: Implementing such an aggregation method preserves the accuracy and capture rates of a clinical decision system, while potentially improving acceptance among healthcare providers. © 2025 The Authors

关键词： Vaccines

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The Reform and Exploration of Undergraduate computer Design in the Background of Engineering Education Professional Certification

The Reform and Exploration of Undergraduate Computer Design ...

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2022年第二届高校教育发展与信息技术创新国际学术会议

作者： Xulei Yu Xiangze Li School of Information and Control Shenyang Institute of Technology School of Computer Science and Engineering Northeasterm University

Graduation design is an important practical teaching link in the training process of engineering undergraduates,which plays a very important role in cultivating students' professional comprehensive ***'s engineering education certification standards put forward a new series of requirements for graduation *** design is an important indicator of certification assessment and *** quality of graduation design has an important impact on the achievement of students' graduation *** paper analyzes the problems and reasons of graduation design from the aspects of design topic selection,project research and quality *** on the student-centered teaching concept,combined with the undergraduate tutorial system,with the goal of improving the students' professional comprehensive ability,the corresponding graduation design teaching reform scheme and the management mode throughout the whole process are proposed to improve the training quality of the engineering graduation design practice teaching link.

关键词： Professional certification of engineering education Bachelor of computer science Graduation design

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Language-driven Grasp Detection with Mask-guided Attention

Language-driven Grasp Detection with Mask-guided Attention

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Tuan Van Vo Minh Nhat Vu Baoru Huang An Vuong Ngan Le Thieu Vo Anh Nguyen FPT Software AI Center Vietnam Automation & Control Institute TU Wien Austria Austrian Institute of Technology (AIT) GmbH Austria Imperial College London UK Department of Computer Science & Computer Engineering University of Arkansas USA National University of Singapore Singapore Department of Computer Science University of Liverpool UK

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Grasp detection is an essential task in robotics with various industrial applications. However, traditional methods often struggle with occlusions and do not utilize language for grasping. Incorporating natural language into grasp detection remains a challenging task and largely unexplored. To address this gap, we propose a new method for language-driven grasp detection with mask-guided attention by utilizing the transformer attention mechanism with semantic segmentation features. Our approach integrates visual data, segmentation mask features, and natural language instructions, significantly improving grasp detection accuracy. Our work introduces a new framework for language-driven grasp detection, paving the way for language-driven robotic applications. Intensive experiments show that our method outperforms other recent baselines by a clear margin, with a 10.0% success score improvement. We further validate our method in real-world robotic experiments, confirming the effectiveness of our approach.

关键词： Visualization Attention mechanisms Accuracy Service robots Source coding Semantic segmentation Natural languages Grasping Transformers Feature extraction

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3DOS: Towards 3D Open Set Learning – Benchmarking and Understanding Semantic Novelty Detection on Point Clouds

arXiv

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arXiv 2022年

作者： Alliegro, Antonio Borlino, Francesco Cappio Tommasi, Tatiana Department of Control and Computer Engineering Politecnico di Torino Italy Italian Institute of Technology Italy

In recent years there has been significant progress in the field of 3D learning on classification, detection and segmentation problems. The vast majority of the existing studies focus on canonical closed-set conditions, neglecting the intrinsic open nature of the real-world. This limits the abilities of robots and autonomous systems involved in safety-critical applications that require managing novel and unknown signals. In this context exploiting 3D data can be a valuable asset since it provides rich information about the geometry of perceived objects and scenes. With this paper we provide the first broad study on 3D Open Set learning. We introduce 3DOS: a novel testbed for semantic novelty detection that considers several settings with increasing difficulties in terms of semantic (category) shift, and covers both in-domain (synthetic-to-synthetic, real-to-real) and cross-domain (synthetic-to-real) scenarios. Moreover, we investigate the related 2D Open Set literature to understand if and how its recent improvements are effective on 3D data. Our extensive benchmark positions several algorithms in the same coherent picture, revealing their strengths and limitations. The results of our analysis may serve as a reliable foothold for future tailored 3D Open Set methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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Ripple Analysis and Reduction of a Dual-PM Direct-Drive Machine by a Harmonic Current Injection Approach 26

Ripple Analysis and Reduction of a Dual-PM Direct-Drive Mach...

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26th International Conference on Electrical Machines and Systems, ICEMS 2023

作者： Ma, Yue Niu, Shuangxia Fu, Weinong Fei, Jiaqi Huang, Jiahui The Hong Kong Polytechnic University Electrical and Electronics Engineering Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Computer Science and Control Engineering Shenzhen China Han's Robot Algorithm Team Han's Laser Smart Equipment Group Co Ltd Shenzhen China

ISBN: (纸本)9798350317589

The Dual permanent magnet machine (DPMM) possesses the characteristics of high torque and low speed which is suitable for direct-drive equipment. Because of the low magnetic reluctance of this motor, the torque is very sensitive to dimensional fluctuations. As a synchronous motor, it also suffers from noise and vibration caused by torque ripple. This research analyzes the torque ripple in several different scenarios under the same DPMM electromagnetic design and finds a predictable influence of mechanical tolerances on torque ripple. In order to reduce the torque ripples, this paper proposes a harmonic current injection (HCI) method. A DPMM with a split-tooth structure is simulated and tested in this paper to demonstrate the analysis of torque fluctuations and the effectiveness of HCI. © 2023 IEEE.

关键词： Torque

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Random Forest Regression for Battery State-of-Health Estimation Based on Unsupervised Transfer Component Analysis Domain Adaptation

Random Forest Regression for Battery State-of-Health Estimat...

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2022 IEEE International Conference on Industrial technology, ICIT 2022

作者： Tian, Jilun Zhang, Jiusi Huangy, Congsheng Chowz, Mo-Yuen Luo, Hao Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China National Taipei University of Technology Department of Electrical Engineering Taipei10608 Taiwan North Carolina State University Department of Electrical and Computer Engineering RaleighNC27606 United States

ISBN: (纸本)9781728119489

Machine learning is an useful approach estimating the state-of-health (SOH) of the lithium-ion batteries and had been successfully implemented on battery management systems (BMS). However, the SOH estimation accuracy of the machine learning relies highly on the similarity of training dataset and battery data of estimation. In other words, the machine learning approach may fail if the battery of estimation is operated in a different condition from the condition set for collecting the training dataset. This paper aims on solving such a problem by proposing a transfer component analysis-random forest regression (TCA-RF) approach. The robustness of this proposed approach is ensured by the random forest regression, which is an ensemble learning approach. The generalization of this proposed approach is enhanced by transfer component analysis since it achieves the domain adaption with well transformation of features between two datasets. Two battery ageing datasets collected in different operating conditions are selected in this paper to validate the success of the proposed work, where these two datasets are collected by the Center for Advanced Life Cycle Engineering (CALCE) and the National Aeronautics and Space Administration (NASA) Prognostics Center of Excellence (PCoE). The proposed work is further compared with multiple commonly adopted intelligent algorithms to showcase the high performance of the proposed work. The experimental results shows that the proposed TCA-RF approach has a better accurate SOH estimation comparing to other estimation algorithms by 2% to more 50%. © 2022 IEEE.

关键词： Lithium-ion batteries

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Advancing Virtual Reality Interaction: A Ring-Shaped controller and Pose Tracking

Advancing Virtual Reality Interaction: A Ring-Shaped Control...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhuqing Zhang Dongxuan Li Jiayao Ma Yijia He Pan Ji Rong Xiong Hongdong Li Yue Wang State Key Laboratory of Industrial Control Technology and Institute of Cyber-Systems and Control Zhejiang University Zhejiang China Tencent Holdings Tencent XR Vision Labs Shenzhen China College of Engineering and Computer Science Australian National University Canberra

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Ensuring robust tracking of controllers’ movement is critical for human-robot interaction in virtual reality (VR) scenarios. This paper proposes a robust tracking algorithm based on a novel wearable ring-shaped controller equipped with an inertial measurement unit (IMU) and a light-emitting diode (LED). This novel controller design allows users to free up their hands for more immersive experiences. To track the controller’s motion accurately and robustly, we resort to various forms of visual measurements, including 6 DoF and 5 DoF pose measurements from hand gesture detection, as well as 3 DoF position measurement and 2 DoF image measurement derived from the LED. We theoretically analyze the performances of these observation models and propose an optimal observation model combination scheme. Moreover, the necessity and rationale of online estimating system gravity are illustrated. The effectiveness of our tracking method is validated through extensive experiments.

关键词： Solid modeling Analytical models Visualization Measurement units Tracking Virtual reality Inertial navigation

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HGS-Planner: Hierarchical Planning Framework for Active Scene Reconstruction Using 3D Gaussian Splatting

arXiv

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arXiv 2024年

作者： Xu, Zijun Jin, Rui Wu, Ke Zhao, Yi Zhang, Zhiwei Zhao, Jieru Gao, Fei Gan, Zhongxue Ding, Wenchao The Academy for Engineering & Technology Fudan University Shanghai200433 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China The Department of Computer Science and Engineering Shanghai Jiao Tong University China

In complex missions such as search and rescue, robots must make intelligent decisions in unknown environments, relying on their ability to perceive and understand their surroundings. High-quality and real-time reconstruction enhances situational awareness and is crucial for intelligent robotics. Traditional methods often struggle with poor scene representation or are too slow for real-time use. Inspired by the efficacy of 3D Gaussian Splatting (3DGS), we propose a hierarchical planning framework for fast and high-fidelity active reconstruction. Our method evaluates completion and quality gain to adaptively guide reconstruction, integrating global and local planning for efficiency. Experiments in simulated and real-world environments show our approach outperforms existing real-time methods. Copyright © 2024, The Authors. All rights reserved.

关键词： 3D reconstruction

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Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements 36

Digital Map Generation Workflow Demonstrated on ZalaZONE Aut...

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36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Somogyi, Árpád Tettamanti, Tamás Varga, Pál Szalay, Zsolt Baranyai, Dániel Lovas, Tamás Budapest University of Technology and Economics Fac. of Civil Engineering Dept. of Photogrammetry and Geoinformatics Budapest Hungary Institute for Computer Science and Control The Eötvös Loránd Research Network Systems and Control Laboratory Budapest Hungary Budapest University of Technology and Economics Fac. of Electrical Engineering and Informatics Dept. of Telecommunications and Media Informatics Budapest Hungary Budapest University of Technology and Economics Fac. of Transportation Eng. and Vehicle Eng. Dept. of Automotive Technologies Budapest Hungary

ISBN: (纸本)9781665477161

One major goal of digital twin technology applied in the Architecture, Engineering, and Construction (AEC) Industry is the mapping of roads and road environments with their associated information. Such digital twins can support cost-effective testing, simulations, and the production of mapping backgrounds for automated vehicles and generally for Cooperative, Connected and Automated Mobility (CCAM) developments. The efficient workflow that leads from data acquisition to finished products depends on a number of requirements and knowledge sets. The main contribution of the paper is a general methodology of creating HD-map from point cloud and image data set. Accordingly, the most widely used survey techniques are presented and the requirements for the objects to be derived are summarized. The paper then outlines a general implementation procedure as an expert knowledge through a real-life example, where the results obtained for the ZalaZONE Automotive Proving Ground are demonstrated. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Stabilization of hyperbolic reaction-diffusion systems on directed networks through the generalized Routh-Hurwitz criterion for complex polynomials

arXiv

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arXiv 2024年

作者： Muolo, Riccardo Hastir, Anthony Nakao, Hiroya Department of Systems and Control Engineering Tokyo Institute of Technology Japan Department of Mathematics and Computer Science Bergische Universität Wuppertal Germany Department of Mathematics and naXys Namur Institute for Complex Systems University of Namur Belgium

The study of dynamical systems on complex networks is of paramount importance in engineering, given that many natural and artificial systems find a natural embedding on discrete topologies. For instance, power grids, chemical reactors and the brain, to name a few, can be modeled through the network formalism by considering elementary units coupled via the links. In recent years, scholars have developed numerical and theoretical tools to study the stability of those coupled systems when subjected to perturbations. In such framework, it was found that asymmetric couplings enhance the possibilities for such systems to become unstable. Moreover, in this scenario the polynomials whose stability needs to be studied bear complex coefficients, which makes the analysis more difficult. In this work, we put to use a recent extension of the well-known Routh-Hurwitz stability criterion, allowing to treat the complex coefficient case. Then, using the Brusselator model as a case study, we discuss the stability conditions and the regions of parameters when the networked system remains stable. © 2024, CC BY.

关键词： Complex networks

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