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    University of British Columbia Reports Findings in Machine Learning (Machine Learning to Predict the Need for Postmastectomy Radiotherapy after Immediate Breast Reconstruction)

    64-65页
    查看更多>>摘要:New research on Machine Learning is the subject of a report. According to news reporting originating from Vancouver, Canada, by NewsRx correspondents, research stated, "Post mastectomy radiotherapy (PMRT) is an independent predictor of reconstructive complications. PMRT may alter the timing and type of reconstruction recommended." Financial support for this research came from Canadian Foundation for Innovation.

    Princess Grace Hospital Reports Findings in Endometriosis (Robotic surgery for bowel endometriosis: a multidisciplinary management of a complex entity)

    65-66页
    查看更多>>摘要:New research on Uterine Diseases and Conditions - Endometriosis is the subject of a report. According to news reporting originating in London, United Kingdom, by NewsRx journalists, research stated, "Bowel endometriosis impacts quality of life. Treatment requires complex surgical procedures with associated morbidity." The news reporters obtained a quote from the research from Princess Grace Hospital, "Precision approach with robotic surgery leads to organ preservation. Bowel endometriosis requires a multidisciplinary management to improve patient outcomes. This study evaluates perioperative outcomes of bowel endometriosis undergoing multidisciplinary planning and robotic surgery. Consecutive cases of multidisciplinary robotic bowel endometriosis procedures (January 2021-December 2022) were evaluated from a prospectively maintained database in a national endometriosis accredited centre. Patients were managed through a multidisciplinary setting including gynaecologists, colorectal robotic surgeons, and other specialists. Dyschezia (menstrual and non-cyclical) and quality of life were assessed pre- and postoperatively (6 months) through validated questionnaires. Sixty-eight consecutive cases of robotic bowel endometriosis were included. Median age was 35.0 (30.2-42.0) years. Median body mass index was 24.0 (21.0-26.7) kg/m. Procedures performed were 48 (70.6%) shavings, 11 (16.2%) deep shavings, 3 (4.4%) disc excisions, and 6 (8.8%) segmental resections. One (1.5%) patient required temporary stoma. Median operating time was 150 (120-180) min. There were no conversions/return to theatre postoperatively. Median endometriotic nodule size was 25.0 (15.5-40.0) mm. Two (2.9%) patients developed postoperative complications. Median length of postoperative stay was 2 (2-4) days. Median follow-up was 12 (7-17) months. One (1.5%) patient recurred. Median menstrual dyschezia score improved from 5.0 (2.0-8.0) to 1.0 (0.0-5.7). Median non-cyclical dyschezia significantly improved (p <0.001) from 1.0 (0.0-5.7) to 0.0 (0.0-2.0). Median quality of life score improved from 52.5 (35.0-70.0) to 74.5 (60.0-80.0)."

    New Machine Learning Study Results Reported from University of Sao Paulo (An Evaluation of Iron Ore Characteristics Through Machine Learning and 2-d Lidar Technology)

    66-67页
    查看更多>>摘要:Investigators discuss new findings in Machine Learning. According to news reporting originating from Sao Carlos, Brazil, by NewsRx correspondents, research stated, "Conveyor belts are the most effective way to transport ore in a mining complex. The ore that comes from the mining areas can be heterogeneous in size and type." Our news editors obtained a quote from the research from the University of Sao Paulo, "As the ore has to pass through several processing stages, online information about the ore type and degree of fragmentation can help improve mineral processing for both safety and efficiency. Current instrumentation systems are expensive and require frequent calibration and maintenance. This article presents a novel intelligent instrument for online recognition of type and degree of fragmentation. A 2-D light detection and ranging (LiDAR) sensor along with machine learning (ML) techniques was used to estimate the characteristics of iron ore particles on conveyor belts. An experiment was conducted using several types of ore and granulometry. Five ML models were compared by means of statistical methods, including average accuracy and normality and hypothesis tests. Among them, the random forest (RF) models achieved the highest rate of accuracy, 93.81% for ore type and 85.52% for degree of fragmentation. These models were improved by a voting mechanism that resulted in a reduction of classification errors of 93.3% for ore type and 99.2% for degree of fragmentation."

    New Artificial Intelligence Study Findings Recently Were Published by Researchers at Chongqing Chemical Industry Vocational College (Development of novel computational models based on artificial intelligence technique to predict the viscosity ...)

    67-68页
    查看更多>>摘要:Fresh data on artificial intelligence are presented in a new report. According to news reporting out of Chongqing, People's Republic of China, by NewsRx editors, research stated, "This paper delves into the practical application of K-Nearest Neighbors (KNN), Kernel Ridge Regression (KRR), and Lasso Regression for the prediction of viscosity of ionic liquids in a dataset characterized by categorical variables (Cation, Anion) and numeric variables (T(K), xIL(mol%))." The news journalists obtained a quote from the research from Chongqing Chemical Industry Vocational College: "Indeed, mole percentage of ionic liquids and temperature were considered as inputs for the models. The models' effectiveness is rigorously assessed, with K-Nearest Neighbors notably exhibiting exceptional predictive performance. To enhance model accuracy, Tabu Search is employed as an optimization tool for hyperparameter tuning. Numeric results showcase KNN's superiority, supported by a remarkable R2 test score of 0.91628 and the lowest RMSE among the models. Tabu Search optimization further refines model performance, emphasizing the critical role of hyperparameter tuning in achieving robust regression models in predicting the viscosity of ionic liquid-water mixtures."

    Findings from University of Bristol in the Area of Machine Learning Described [Das-n2n: Machine Learning Distributed Acoustic Sensing (Das) Signal Denoising Without Clean Data]

    68-69页
    查看更多>>摘要:Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Bristol, United Kingdom, by NewsRx correspondents, research stated, "This paper presents a weakly supervised machine learning method, which we call DAS-N2N, for suppressing strong random noise in distributed acoustic sensing (DAS) recordings. DAS-N2N requires no manually produced labels (i.e. pre-determined examples of clean event signals or sections of noise) for training and aims to map random noise processes to a chosen summary statistic, such as the distribution mean, median or mode, whilst retaining the true underlying signal."

    Findings on Machine Learning Discussed by Investigators at Indian Institute of Astrophysics (Possibilities of Identifying Members From Milky Way Satellite Galaxies Using Unsupervised Machine Learning Algorithms)

    69-70页
    查看更多>>摘要:Research findings on Machine Learning are discussed in a new report. According to news originating from Bangalore, India, by NewsRx correspondents, research stated, "A detailed study of stellar populations in Milky Way (MW) satellite galaxies remains an observational challenge due to their faintness and fewer spectroscopically confirmedmember stars. We use unsupervised machine learning methods to identify new members for nine nearby MW satellite galaxies using Gaia data release-3 (Gaia DR3) astrometry, the Dark Energy Survey (DES) and the DECam Local Volume Exploration Survey (DELVE) photometry."

    Investigators from University of Alabama Birmingham Report New Data on Machine Learning (Machine Learning the Relationship Between Debye Temperature and Superconducting Transition Temperature)

    70-70页
    查看更多>>摘要:Researchers detail new data in Machine Learning. According to news reporting out of Birmingham, Alabama, by NewsRx editors, research stated, "Recently a relationship between the Debye temperature OD and the superconducting transition temperature Tc of conventional superconductors has been proposed [Esterlis et al., npj Quantum Mater. 3, 59 (2018)]. The relationship indicates that Tc AOD for phonon-mediated BCS superconductors, with A being a prefactor of order -0.1." Funders for this research include National Science Foundation (NSF), UAB Blazer Fellowship, FTPP CERIF Graduate Research Assistantship, National Science Foundation (NSF), United States Department of Energy (DOE), ADECA.

    New Findings from Harbin Institute of Technology in the Area of Robotics Reported (A Miniature Water Jumping Robot Based On Accurate Interaction Force Analysis)

    71-71页
    查看更多>>摘要:Research findings on Robotics are discussed in a new report. According to news reporting originating in Harbin, People's Republic of China, by NewsRx journalists, research stated, "Water jumping motion extends the robot's movement space and flexibility. However, the jumping performance is influenced by multiple factors such as driving force, rowing trajectory, and robot structure." Financial support for this research came from Equipment Pre-Research Application Innovation Project. The news reporters obtained a quote from the research from the Harbin Institute of Technology, "The interaction force between the robot and water surface is complicated due to water deformation, and the difficulty of the water jumping increases with the robot's scale. This article designs a miniature water jumping robot with rowing driving legs. The hydrodynamic model between driving legs and water is established based on the modified Wagner theory with consideration of water surface deformation. Particularly, the dynamic model of the robot for the whole jumping process is also developed related to multiple factors. Then, the jumping performance is improved by optimizing the energy storage modality, rowing trajectory, and supporting leg shapes through the theoretical analysis and experiments. The fabricated robot weights 91 g, and its length, width, and height are 220, 410, and 95 mm, respectively."

    Xiangtan University Researchers Target Robotics (A Lightweight Operation Mode Decision Method for Cleaning Robots Driven by Garbage Attributes Perception)

    72-72页
    查看更多>>摘要:Researchers detail new data in robotics. According to news originating from Xiangtan, People's Republic of China, by NewsRx editors, the research stated, "The intelligent operation mode decision scheme has been proved to be a promising solution for enhancing the cleaning performance of cleaning robots." Financial supporters for this research include Joint Fund For Rural Innovation And Development of The National Natural Science Foundation of China; Nsfc; Innovation Platform And Talent Program of Hunan Province.

    First Affiliated Hospital of Soochow University Reports Findings in Prostate Cancer (The practical clinical role of machine learning models with different algorithms in predicting prostate cancer local recurrence after radical prostatectomy)

    73-74页
    查看更多>>摘要:New research on Oncology - Prostate Cancer is the subject of a report. According to news reporting originating from Suzhou, People's Republic of China, by NewsRx correspondents, research stated, "The detection of local recurrence for prostate cancer (PCa) patients following radical prostatectomy (RP) is challenging and can influence the treatment plan. Our aim was to construct and verify machine learning models with three different algorithms based on post-operative mpMRI for predicting local recurrence of PCa after RP and explore their potential clinical value compared with the Prostate Imaging for Recurrence Reporting (PI-RR) score of expert-level radiologists."