首页期刊导航|Robotics & Machine Learning Daily News
期刊信息/Journal information
Robotics & Machine Learning Daily News
NewsRx
Robotics & Machine Learning Daily News

NewsRx

Robotics & Machine Learning Daily News/Journal Robotics & Machine Learning Daily News
正式出版
收录年代

    Free University Bolzano Details Findings in Artificial Intelligence (Artificial Intelligence In Healthcare Institutions: a Systematic Literature Review On Influencing Factors)

    58-58页
    查看更多>>摘要：Current study results on Artificial Intelligence have been published. According to news reporting originating in Bolzano, Italy, by NewsRx journalists, research stated, "The purpose of this review is integrating and contextualizing relevant literature on the factors influencing the adoption of AI in the healthcare industry into a comprehensive framework. Health systems are considered fundamental to creating societal value." The news reporters obtained a quote from the research from Free University Bolzano, "However, global health systems are challenged by the increasing number of patients due to population aging and the growing prevalence of chronic diseases and cancer. Meanwhile, the United Nations calls for equal access to healthcare, tackling costs, and addressing resource constraints to foster the sustainable development of societies. In this context, artificial intelligence (AI) is gaining attention as it constitutes a promising technology to address these burgeoning challenges. Despite opportunities, the literature specifically on the adoption of AI in the healthcare industry is fragmented across various research fields, lacking a comprehensive overview. It lacks theoretically grounded research integrating, for example, the factors that influence the adoption of AI in healthcare institutions.Derived from a multi-disciplinary systematic literature review, building on 130 studies, we propose the Adoption of AI in the Healthcare Industry Model. This model encompasses five dimensions influencing the adoption of AI in the healthcare industry and contextualizes them. We propose that macro-economic, regulatory, and technological readiness serve as external antecedents whereas organizational and individual readiness constitute internal antecedents influencing adoption of AI in healthcare institutions.Our review has implications for research on technology acceptance related to AI in healthcare."
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    University of Missouri Researcher Yields New Study Findings on Machine Learning (Machine Learning for Modeling Oscillating Heat Pipes: A Review)

    59-59页
    查看更多>>摘要：New research on artificial intelligence is the subject of a new report. According to news reporting originating from the University of Missouri by NewsRx correspondents, research stated, "Oscillating heat pipes are heat transfer devices with the potential of addressing some of the most pressing current thermal management problems, from the miniaturization of microchips to the development of hypersonic vehicles." Financial supporters for this research include Office of Naval Research. The news reporters obtained a quote from the research from University of Missouri: "Since their invention in the 1990s, numerous studies have attempted to develop predictive and inverse design models for oscillating heat pipe function. However, the field still lacks robust and flexible models that can be used to prescribe design specifications based on a target performance. The fundamental difficulty lies in the fact that, despite the simplicity of their design, the mechanisms behind the operation of oscillating heat pipes are complex and only partially understood. To circumvent this limitation, over the last several years, there has been increasing interest in the application of machine learning techniques to oscillating heat pipe modeling. Our survey of the literature has revealed that machine learning techniques have successfully been used to predict different aspects of the operation of these devices. However, many fundamental questions such as which machine learning models are better suited for this task or whether their results can extrapolate to different experimental setups remain unanswered."
      原文链接:
    • NETL
    • NSTL
    • Asme

    Max-Planck-Institute for Coal Research Reports Findings in Artificial Intelligence (Materials Genes of CO2 Hydrogenation on Supported Cobalt Catalysts: An Artificial Intelligence Approach Integrating Theoretical and Experimental Data)

    60-60页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting out of Mulheim an der Ruhr, Germany, by NewsRx editors, research stated, "Designing materials for catalysis is challenging because the performance is governed by an intricate interplay of various multiscale phenomena, such as the chemical reactions on surfaces and the materials' restructuring during the catalytic process. In the case of supported catalysts, the role of the support material can be also crucial." Our news journalists obtained a quote from the research from Max-Planck-Institute for Coal Research, "Here, we address this intricacy challenge by a symbolic-regression artificial intelligence (AI) approach. We identify the key physicochemical parameters correlated with the measured performance, out of many offered candidate parameters characterizing the materials, reaction environment, and possibly relevant underlying phenomena. Importantly, these parameters are obtained by both experiments and ab initio simulations. The identified key parameters might be called 'materials genes', in analogy to genes in biology: they correlate with the property or function of interest, but the explicit physical relationship is not (necessarily) known. To demonstrate the approach, we investigate the CO hydrogenation catalyzed by cobalt nanoparticles supported on silica. Crucially, the silica support is modified with the additive metals magnesium, calcium, titanium, aluminum, or zirconium, which results in six materials with significantly different performances. These systems mimic hydrothermal vents, which might have produced the first organic molecules on Earth. The key parameters correlated with the CHOH selectivity reflect the reducibility of cobalt species, the adsorption strength of reaction intermediates, and the chemical nature of the additive metal. By using an AI model trained on basic elemental properties of the additive metals (e.g., ionization potential) as physicochemical parameters, new additives are suggested."
      原文链接:
    • NETL
    • NSTL

    Data on Endometriosis Reported by Adrien Crestani and Colleagues (Outcomes of discoid excision and segmental resection for colorectal endometriosis: robotic versus conventional laparoscopy)

    61-61页
    查看更多>>摘要：New research on Uterine Diseases and Conditions - Endometriosis is the subject of a report. According to news originating from Bordeaux, France, by NewsRx correspondents, research stated, "Surgery for deep endometriosis with colorectal involvement is an option after medical treatment failure. Over the past decade, robotic laparoscopy has emerged as an alternative to conventional laparoscopy." Our news journalists obtained a quote from the research, "We aimed to evaluate surgical outcomes of robotic versus conventional laparoscopy for discoid excision and segmental resection. From 2019 to 2023, we conducted a retrospective cohort study of 152 consecutive patients with colorectal endometriosis who underwent robotic or conventional laparoscopy for discoid excision and colorectal resection. Ninety of the patients 152 underwent robotic surgery and 62 conventional laparoscopy. The mean total surgical room occupancy and operating times were longer in the robotic group: 270 ± 81 min vs 240 ± 79 min, p = 0.010, and 216 ± 78 min vs 190 ± 76, p = 0.027, respectively. The mean intraoperative blood loss, and the incidence of intra- and postoperative complications (according to Clavien-Dindo classification) were similar in the two groups. The mean hospital stay was greater after conventional laparoscopy (8 ± 5 vs 7 ± 4 days; p = 0.03), and the rate of persistent voiding dysfunction was higher in the conventional group (9/11, 25% vs 2/11, 5%; p = 0.01). A higher incidence of persistent voiding dysfunction was also observed after segmental resection by conventional laparoscopy (25% vs 4.8%, p = 0.01)."
      原文链接:
    • NETL
    • NSTL

    Studies from Jiangxi Normal University Reveal New Findings on Machine Learning [Molecular Dynamics Simulations of Liquid Gallium Alloy Ga-x (X = Pt, Pd, Rh) via Machine Learning Potentials]

    62-63页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting from Nanchang, People's Republic of China, by NewsRx journalists, research stated, "Liquid gallium (Ga) has achieved significant attention across numerous fields in recent decades due to its distinctive physicochemical properties. In particular, the exceptional fluidic nature of liquid Ga makes it an excellent solvent to dissolve transition metals to prepare liquid Ga alloy (LGA) catalytic systems (M. A. Rahim, J. Tang, A. J. Christofferson, P. V. Kumar, N. Meftahi, F. Centurion, Z. Cao, J. Tang, M. Baharfar, M. Mayyas, F.-M. Allioux, P. Koshy, T. Daeneke, C. F. McConville, R. B. Kaner, S. P. Russo and K. Kalantar-Zadeh, Low-Temperature Liquid Platinum Catalyst, Nat." Financial supporters for this research include National Natural Science Foundation of China (NSFC), National Natural Science Foundation of China (NSFC). The news correspondents obtained a quote from the research from Jiangxi Normal University, "Chem., 2022, 14, 935-941). Thus, it is an important scientific quest to understand the microscopic structures and properties of transition metal atoms in LGA. Here, we employed a newly developed machine learningbased moment tensor potential (MTP), combined with molecular dynamics simulations, to explore the coordination and diffusion behaviors of transition metal atoms in three LGA systems of Ga-Pt, Ga-Pd, and Ga-Rh. It is observed that the trained MTP can provide accurate descriptions of energies and forces, as well as local structures, for each LGA system. Besides, our simulation results reveal that the average coordination number of the transition metal atom with surrounding Ga atoms follows an order of Ga-Rh ＞Ga-Pt ＞Ga-Pd, while the diffusion coefficient of the transition metal atom in liquid Ga has an inverse order of Ga-Rh ＜Ga-Pt ＜Ga-Pd. This is primarily because the diffusion barrier of Rh in liquid Ga is maximum, yet that of Pd in liquid Ga is minimum. Furthermore, the results of mean square displacement and the van Hove function suggest a normal diffusion mechanism for all three studied transition metal atoms in liquid Ga."
      原文链接:
    • NETL
    • NSTL
    • Royal Soc Chemistry

    Chulalongkorn University and King Chulalongkorn Memorial Hospital Reports Findings in Sepsis (Real-time machine learning-assisted sepsis alert enhances the timeliness of antibiotic administration and diagnostic accuracy in emergency department …)

    63-64页
    查看更多>>摘要：New research on Blood Diseases and Conditions - Sepsis is the subject of a report. According to news reporting originating from Bangkok, Thailand, by NewsRx correspondents, research stated, "Machine learning (ML) has been applied in sepsis recognition across different healthcare settings with outstanding diagnostic accuracy. However, the advantage of ML-assisted sepsis alert in expediting clinical decisions leading to enhanced quality for emergency department (ED) patients remains unclear." Our news editors obtained a quote from the research from Chulalongkorn University and King Chulalongkorn Memorial Hospital, "A cluster-randomized trial was conducted in a tertiary-care hospital. Adult patient data were subjected to an ML model for sepsis alert. Patient visits were assigned into one of two groups. In the intervention cluster, staff received alerts on a display screen if patients met the ML threshold for sepsis diagnosis, while patients in the control cluster followed the regular alert process. The study compared triage-to-antibiotic (TTA) time, length of stay, and mortality rate between the two groups. Additionally, the diagnostic performance of the ML model was assessed. A total of 256 (intervention) and 318 (control) sepsis patients were analyzed. The proportions of patients who received antibiotics within 1 and 3 h were higher in the intervention group than in the control group (in 1 h; 68.4 vs. 60.1%, respectively; P = 0.04, in 3 h; 94.5 vs. 89.0%, respectively; P = 0.02). The median TTA times were marginally shorter in the intervention group (46 vs. 50 min). The area under the receiver operating characteristic curve (AUROC) of ML in early sepsis identification was significantly higher than qSOFA, SIRS, and MEWS. The ML-assisted sepsis alert system may help sepsis ED patients receive antibiotics more rapidly than with the conventional, human-dedicated alert process. The diagnostic performance of ML in prompt sepsis detection was superior to that of the rule-based system.Trial registration Thai Clinical Trials Registry TCTR20230120001."
      原文链接:
    • NETL
    • NSTL

    Researchers' from Lancaster University Report Details of New Studies and Findings in the Area of Robotics (Improving the kinematic accuracy of a collaborative continuum robot by using flexure-hinges)

    64-64页
    查看更多>>摘要：Investigators publish new report on robotics. According to news reporting originating from Lancaster, United Kingdom, by NewsRx correspondents, research stated, "Within various unstructured industrial environments, there is often the requirement to conduct remote engineering tasks, such as sampling the structure for analysis prior to decommissioning." Funders for this research include Epsrc. The news editors obtained a quote from the research from Lancaster University: "Most existing tools are simply not dexterous enough to fulfil this task, and thus new technology is required. We describe here a simple, lightweight, and water-resistant collaborative dual-arm continuum robot system which can aid in this task. To improve the kinematic accuracy of the system, a class of flexible hinges have been combined with a conventional continuum robot configuration. The thickness and width of said flexible hinges can be adjusted to adapt to various tasks. Kinematic and stiffness models have further been developed, incorporating the influence of these flexible hinges. A set of experiments have been conducted to validate the proposed model and demonstrate the advantages of the platform."
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Data on Machine Learning Described by Researchers at Department of Data Science and Artificial Intelligence (Enhancing digital health services: A machine learning approach to personalized exercise goal setting)

    65-65页
    查看更多>>摘要：New research on artificial intelligence is the subject of a new report. According to news reporting from Melbourne, Australia, by NewsRx journalists, research stated, "The utilization of digital health has increased recently, and these services provide extensive guidance to encourage users to exercise frequently by setting daily exercise goals to promote a healthy lifestyle. These comprehensive guides evolved from the consideration of various personalized behavioral factors." Financial supporters for this research include National Natural Science Foundation of China. The news reporters obtained a quote from the research from Department of Data Science and Artificial Intelligence: "Nevertheless, existing approaches frequently neglect the users' dynamic behavior and the changing in their health conditions. This study aims to fill this gap by developing a machine learning algorithm that dynamically updates auto-suggestion exercise goals using retrospective data and realistic behavior trajectory. We conducted a methodological study by designing a deep reinforcement learning algorithm to evaluate exercise performance, considering fitness-fatigue effects. The deep reinforcement learning algorithm combines deep learning techniques to analyze time series data and infer user's exercise behavior. In addition, we use the asynchronous advantage actor-critic algorithm for reinforcement learning to determine the optimal exercise intensity through exploration and exploitation. The personalized exercise data and biometric data used in this study were collected from publicly available datasets, encompassing walking, sports logs, and running. In our study, we conducted the statistical analyses/inferential tests to compare the effectiveness of machine learning approach in exercise goal setting across different exercise goal-setting strategies. The 95% confidence intervals demonstrated the robustness of these findings, emphasizing the superior outcomes of the machine learning approach."
      原文链接:
    • NETL
    • NSTL
    • Sage

    Research from Universitat Politecnica de Catalunya (UPC) Yields New Findings on Artificial Intelligence (Enhancing the Accuracy of Low-Cost Inclinometers with Artificial Intelligence)

    66-66页
    查看更多>>摘要：Investigators publish new report on artificial intelligence. According to news reporting out of Barcelona, Spain, by NewsRx editors, research stated, "The development of low-cost structural and environmental sensors has sparked a transformation across numerous fields, offering cost-effective solutions for monitoring infrastructures and buildings." Financial supporters for this research include Nation Natural Science Foundation of China. The news correspondents obtained a quote from the research from Universitat Politecnica de Catalunya (UPC): "However, the affordability of these solutions often comes at the expense of accuracy. To enhance precision, the LARA (Low-cost Adaptable Reliable Anglemeter) system averaged the measurements of a set of five different accelerometers working as inclinometers. However, it is worth noting that LARA's sensitivity still falls considerably short of that achieved by other high-accuracy commercial solutions. There are no works presented in the literature to enhance the accuracy, precision, and resolution of low-cost inclinometers using artificial intelligence (AI) tools for measuring structural deformation. To fill these gaps, artificial intelligence (AI) techniques are used to elevate the precision of the LARA system working as an inclinometer."
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Investigators at University of Paris Saclay Discuss Findings in Machine Learning (A Hybrid Machine Learning Unmixing Method for Automatic Analysis of Y-spectra With Spectral Variability)

    67-67页
    查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting originating from Palaiseau, France, by NewsRx correspondents, research stated, "Automatic identification and quantification of y -emitting radionuclides, taking into account spectral deformations due to y - interactions in radioactive source surroundings, is a challenging task in the nuclear field. In that context, this paper presents a Machine Learning approach based on autoencoder that can learn a model for the spectral signatures of y -emitters with variability." Our news editors obtained a quote from the research from the University of Paris Saclay, "Training and test datasets were obtained by means of simulated y -spectra computed with the Geant4 simulation code according to increasing material thicknesses (steel, lead). A novel hybrid unmixing algorithm combining a pretrained autoencoder is studied for joint estimation of spectral signatures and counting in the case of mixtures of four radionuclides (57Co, 60Co, 133Ba, 137Cs). The investigations were carried out to account for spectral deformations due to attenuation, Compton scattering and fluorescence at high and low statistics." According to the news editors, the research concluded: "This study demonstrates the validity of this novel hybrid approach combining Machine Learning and Maximum Likelihood for the automatic full - spectrum analysis of y -spectra."
      原文链接:
    • NETL
    • NSTL
    • Elsevier