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    Department of Radiology Reports Findings in Artificial Intelligence (Automatic diagnosis of Parkinson's disease using artificial intelli- gence base on routine T1-weighted MRI)

    1-2页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting originating from Chongqing, People’s Republic of China, by NewsRx correspondents, research stated, “Parkinson’s disease (PD) is the second most common neurodegenerative disease. An objective diagnosis method is urgently needed in clinical practice.” Financial support for this research came from Fundamental Research Funds for the Central Universities. Our news editors obtained a quote from the research from the Department of Radiology, “In this study, deep learning and radiomics techniques were studied to automatically diagnose PD from healthy controls (HCs). 155 PD patients and 154 HCs were randomly divided into a training set (246 patients) and a testing set (63 patients). The brain subregions identification and segmentation were automatically performed with a VB-net, and radiomics features of billateral thalamus, caudatum, putamen and pallidum were extracted. Five independent machine learning classifiers [Support Vector Machine (SVM), Stochastic gradient descent (SGD), random forest (RF), quadratic discriminant analysis (QDA) and decision tree (DT)] were trained on the training set, and validated on the testing. Delong test was used to compare the performance of different models. Our VB-net could automatically identify and segment the brain into 109 regions. 2,264 radiomics features were automatically extracted from the billateral thalamus, caudatum, putamen or pallidum of each patient. After four step of features dimensionality reduction, Delong tests showed that the SVM model based on combined features had the best performance, with AUCs of 0.988 (95% CI: 0.979 0.998, specificity = 91.1%, sensitivity =100%, accuracy = 89.4% and precision = 88.2%) and 0.976 (95% CI: 0.942 1.000, specificity = 100%, sensitivity = 87.1%, accuracy = 93.5% and precision = 88.6%) in the training set and testing set, respectively. Decision curve analysis showed that the clinical benefit of the line graph model was high. The SVM model based on combined features could be used to diagnose PD with high accuracy. Our fully automatic model could rapidly process the MRI data and distinguish PD and HCs in one minute.”
      原文链接:
    • NETL
    • NSTL
    • Frontiers Media Sa

    Data on Artificial Intelligence Reported by a Researcher at George Mason University (Investigation of Phishing Susceptibility with Explainable Artificial Intelligence)

    2-3页
    查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news reporting from Fairfax, Virginia, by NewsRx journalists, research stated, “Phishing attacks represent a significant and growing threat in the digital world, affecting individuals and organizations globally.” Our news editors obtained a quote from the research from George Mason University: “Understanding the various factors that influence susceptibility to phishing is essential for developing more effective strategies to combat this pervasive cybersecurity challenge. Machine learning has become a prevalent method in the study of phishing susceptibility. Most studies in this area have taken one of two approaches: either they explore statistical associations between various factors and susceptibility, or they use complex models such as deep neural networks to predict phishing behavior. However, these approaches have limitations in terms of providing practical insights for individuals to avoid future phishing attacks and delivering personalized explanations regarding their susceptibility to phishing. In this paper, we propose a machinelearning approach that leverages explainable artificial intelligence techniques to examine the influence of human and demographic factors on susceptibility to phishing attacks. The machine learning model yielded an accuracy of 78%, with a recall of 71%, and a precision of 57%.” According to the news editors, the research concluded: “Our analysis reveals that psychological factors such as impulsivity and conscientiousness, as well as appropriate online security habits, significantly affect an individual’s susceptibility to phishing attacks. Furthermore, our individualized case-by-case approach offers personalized recommendations on mitigating the risk of falling prey to phishing exploits, considering the specific circumstances of each individual.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Researchers from Beijing Academy of Agricultural and Forestry Sciences Describe Findings in Machine Learning (Developing a Comprehensive Evaluation Model of Variety Adaptability Based On Machine Learning Method)

    3-4页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Context or problem: A comprehensive evaluation of the adaptability of maize varieties is very important to accurately promote new varieties and reduce the risk of using them. However, challenges are faced when accurately promoting new varieties owing to the lack of a comprehensive model to evaluate the adaptability of a variety for a specific area, such as a district or county.Objective or research question: The purpose of this study was to construct a new maize (Zea mays) Variety Adaptability Comprehensive Evaluation Index (VACEI) by combining nine agronomic traits; including the lodging rate, stalk rot (Fusarium graminearum) resistance, ear rot (Fusarium graminearum) resistance, Curvularia leaf spot (Curvularia lunata) resistance, southern leaf blight (Bipolaris maydis) resistance, common smut (Ustilago maydis) resistance, southern corn rust (Puccinia polysora) resistance, growth period, and yield; that utilized a machine learning method to construct a prediction model for the VACE and estimate the adaptability of maize varieties on a district or county scale.” Financial support for this research came from Sci-Tech Innovation 2030 Agenda.
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Researchers from Tsinghua University Discuss Findings in Robotics (Inverse-reinforcement-learning-based Robotic Ultrasound Active Compliance Control In Uncertain Environments)

    4-5页
    查看更多>>摘要：Data detailed on Robotics have been presented. According to news originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Robotic ultrasound systems (RUSs) have gained increasing attention because they can automate repetitive procedures and relieve operators’ workloads. However, the complexity and uncertainty of the human surface pose a challenge for stable scanning control.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), China Postdoctoral Science Foundation, National Key Research and Development Program of China, Beijing Natural Science Foundation. Our news journalists obtained a quote from the research from Tsinghua University, “This article proposes a general active compliance control strategy based on inverse reinforcement learning (IRL) to perform adaptable scanning for uncertain and unstructured environments. We analyze the manual scanning process pattern and propose a velocity-and-force-related control strategy to achieve variable force control and handle unpredictable deformation. Then, a hybrid policy optimization framework is proposed to improve transferability. In this framework, a reinforcement learning policy with a predefined reward is built to establish the relationship between contact force and posture. Furthermore, the policy is re-optimized using IRL and generated demonstrations for IRL training. The policy is trained on simple standard phantoms and further evaluated for stability and transferability in unseen and complex environments. Quantitative results show that the difference between the proposed method and the three-dimensional (3-D) reconstructed model in terms of posture is (2.3 +/-1.3 degrees, 1.9 +/-1.2 degrees) in continuous scans.”
      原文链接:
    • NETL
    • NSTL
    • IEEE

    Reports on Machine Learning from Stanford University Provide New Insights (Lessons Learned From a Multi-site, Team-based Serious Illness Care Program Implementation At an Academic Medical Center)

    5-6页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting originating in Stanford, California, by NewsRx journalists, research stated, “Patients with serious illness benefit from conversations to share prognosis and explore goals and values. To address this, we implemented Ariadne Labs’ Serious Illness Care Program (SICP) at Stanford Health Care.” Financial support for this research came from Stanford Department of Medicine. The news reporters obtained a quote from the research from Stanford University, “Improve quantity, timing, and quality of serious illness conversations. Initial implementation followed Ariadne Labs’ SICP framework. We later incorporated a team-based approach that included nonphysician care team members. Outcomes included number of patients with documented conversations according to clinician role and practice location. Machine learning algorithms were used in some settings to identify eligible patients. Ambulatory oncology and hospital medicine were our largest implementation sites, engaging 4707 and 642 unique patients in conversations, respectively. Clinicians across eight disciplines engaged in these conversations. Identified barriers that included leadership engagement, complex workflows, and patient identification.” According to the news reporters, the research concluded: “Several factors contributed to successful SICP implementation across clinical sites: innovative clinical workflows, machine learning based predictive algorithms, and nonphysician care team member engagement.”
      原文链接:
    • NETL
    • NSTL
    • Mary Ann Liebert, Inc

    Studies from Shibaura Institute of Technology Reveal New Findings on Robotics (The Influence of Micro-Hexapod Walking-Induced Pose Changes on LiDAR-SLAM Mapping Performance)

    6-7页
    查看更多>>摘要：Research findings on robotics are discussed in a new report. According to news originating from Tokyo, Japan, by NewsRx editors, the research stated, “Micro-hexapods, well-suited for navigating tight or uneven spaces and suitable for mass production, hold promise for exploration by robot groups, particularly in disaster scenarios.” Financial supporters for this research include Jsps Kakenhi. The news reporters obtained a quote from the research from Shibaura Institute of Technology: “However, research on simultaneous localization and mapping (SLAM) for micro-hexapods has been lacking. Previous studies have not adequately addressed the development of SLAM systems considering changes in the body axis, and there is a lack of comparative evaluation with other movement mechanisms. This study aims to assess the influence of walking on SLAM capabilities in hexapod robots. Experiments were conducted using the same SLAM system and LiDAR on both a hexapod robot and crawler robot. The study compares map accuracy and LiDAR point cloud data through pattern matching. The experimental results reveal significant fluctuations in LiDAR point cloud data in hexapod robots due to changes in the body axis, leading to a decrease in map accuracy.” According to the news editors, the research concluded: “In the future, the development of SLAM systems considering body axis changes is expected to be crucial for multi-legged robots like micro-hexapods. Therefore, we propose the implementation of a system that incorporates body axis changes during locomotion using inertial measurement units and similar sensors.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Study Findings on Machine Learning Reported by Researchers at Universitas Bina Darma (Machine Learning-Based E-Archive for Archives Management of South Sumatra Province)

    7-7页
    查看更多>>摘要：Current study results on artificial intelligence have been published. According to news reporting from the Universitas Bina Darma by NewsRx journalists, research stated, “Archives play a crucial role in institutional operations, yet efficiently retrieving specific information from them can be challenging.” The news editors obtained a quote from the research from Universitas Bina Darma: “This research addresses this issue by developing an information retrieval system that incorporates advanced methods to enhance search efficiency. The system employs the TF-IDF (Term Frequency-Inverse Document Frequency) formula, which assesses the significance of a word within a document set, and the BM25 method, a sophisticated algorithm for ranking documents based on their relevance to the input query. Both methods undergo a preprocessing stage, enabling the system to calculate the relevance of each document to the given query accurately. The effectiveness of this system is evaluated using key performance metrics: precision (accuracy), recall (completeness), and the F1 Score (the harmonic means of precision and recall, representing the best value). Testing with various keywords revealed that the BM25 method yielded impressive results, achieving an average precision of 0.75, recall of 0.6, and an F1 Score of 0.6665. In contrast, the TF-IDF method scored lower, with a precision of 0.33, recall of 0.2, and an F1 Score of 0.2500.”
      原文链接:
    • NETL
    • NSTL

    Findings from Qingdao University Provide New Insights into Androids (Customer Acceptance of Frontline Social Robots-humanrobot Interaction As Boundary Condition)

    8-8页
    查看更多>>摘要：Investigators publish new report on Robotics - Androids. According to news reporting from Qingdao, People’s Republic of China, by NewsRx journalists, research stated, “From an interactionist perspective, we argue that what happens and how service is delivered during the humanrobot interaction may alter the extent to which customers accept service robots. Extending previous research on customer acceptance of service robots and human-robot interaction, we treat the elements during the humanrobot interaction process as boundary conditions for the link between service robots’ functional and socialemotional capabilities.” Funders for this research include Shandong Provincial Natural Science Foundation for Excellent Young Scholars, Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China, Natural Science Foundation of Shandong Province. The news correspondents obtained a quote from the research from Qingdao University, “Specifically, we examine (1) contact frequency between customers and service robots, (2) interdependence among service robots and human service employees, and (3) service complexity, moderate the relationship between service robots’ capabilities and customer acceptance. With data collected from 997 customers who have past experience with service robots, we found that the effect of functional and socialemotional capabilities of service robots on customer acceptance are more salient when contact frequency is low rather than high, interdependence among service robots and service employees is high rather than low, and service complexity is low rather than high.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    New Robotics Study Findings Reported from University of Alberta (Target-path Planning and Manufacturability Check for Robotic Clt Machining Operations From Bim Information)

    9-9页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news originating from Edmonton, Canada, by NewsRx correspondents, research stated, “Mass timber is one of the trending construction styles in the last years thanks to its sustainability and offsite manufacturing properties, where cross laminated timber (CLT) is the most common material used. In an effort to link design and manufacturing information in a single location, this study proposes a generative process planning algorithm for CLT machining in robotic environments.” Financial supporters for this research include SMART Lab at the University of Alberta, CGIAR. Our news journalists obtained a quote from the research from the University of Alberta, “The algorithm focuses on automatic feature-based interpretation of the geometry of CLT panels to obtain the targets required to guide the robots for its machining. The method developed detects primitives geometries of the CLT panels, determines the appropriate operations (either sawing, drilling, or milling), select the robot based on manufacturing capabilities (reach and tool availability), and generates the target-path planning for its machining process. The proposed method is tested in a robotic machining station for CLT panels simulated in RobotStudio ® as a case study. The results showcase the capabilities of the proposed algorithm to provide manufacturing results out of the process planning process from geometric information available at the design stage. These results include process duration, path planning, resource allocation and utilization.” According to the news editors, the research concluded: “This study provides a framework to include manufacturing information in design decisions to facilitate planning or cost estimations and anticipate issues downstream generated during the design phase.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Findings in the Area of Machine Learning Reported from University of Vigo (Decentralized and Collaborative Machine Learning Framework for Iot)

    10-11页
    查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting originating from Vigo, Spain, by NewsRx correspondents, research stated, “Decentralized machine learning has recently been proposed as a potential solution to the security issues of the canonical federated learning approach. In this paper, we propose a decentralized and collaborative machine learning framework specially oriented to resource-constrained devices, usual in IoT deployments.” Funders for this research include Axencia Galega de Innovacion (GAIN), Agencia Estatal de Investigacion under the research project “Enhancing Communication Protocols with Machine Learning while Protecting Sensitive Data (COMPROMISE). Our news editors obtained a quote from the research from the University of Vigo, “With this aim we propose the following construction blocks. First, an incremental learning algorithm based on prototypes that was specifically implemented to work in low-performance computing elements. Second, two randombased protocols to exchange the local models among the computing elements in the network. Finally, two algorithmics approaches for prediction and prototype creation.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier