查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Artificial In telligence have been published. According to news reporting originating from Bri sbane, Australia, by NewsRx correspondents, research stated, “In response to the burgeoning interest in the Metaverse-a virtual reality-driven immersive digital world-this study delves into the pivotal role of AI in shaping its functionalit ies and elevating user engagement. Focused on recent advancements, prevailing ch allenges, and potential future developments, our research draws from a comprehen sive analysis grounded in meticulous methodology.” Financial supporters for this research include Australian Research Council, Quee nsland University of Technology.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Technology - Digital T echnology is the subject of a report. According to news reporting originating in Vienna, Austria, by NewsRx journalists, research stated, “Many factors need to be considered when selecting treatment protocol for surgical correction of skele tal open bite deformities. In order to achieve stable long-term results, it is e ssential to explore the origin of the open bite, including dysfunction of the te mporomandibular joint, tongue and compromised nasal breathing, in addition to th e skeletal deformity.” The news reporters obtained a quote from the research from the Medical Universit y of Vienna, “Recurrence of skeletal open bite is associated with relapse of the expanded transverse width. Three-dimensional virtual planning allows different treatment options to be explored and final decisions to be made together with th e orthodontist. This study presents a treatment protocol for predictable and sta ble widening of the maxillary transverse width over the long term, involving pre molar extraction and rounding and shortening of the upper dental arch by advanci ng the molar segments. The stability of inter-canine, inter-premolar, and inter- molar distances, as well as overjet and overbite, were measured in 16 patients t reated with this technique; measurements were obtained pre- and post-surgery, an d the mean follow-up was 43 months. Orthodontic treatment was designed digitally and finished with robotically bent wires (SureSmile), which allowed exact plann ing of the overall treatment, thus making orthognathic surgery more predictable for the patient.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Skin Diseases and Cond itions - Dermatitis is the subject of a report. According to news reporting out of Nicosia, Cyprus, by NewsRx editors, research stated, “Acute radiation dermati tis (ARD) is a common and distressing issue for cancer patients undergoing radia tion therapy, leading to significant morbidity. Despite available treatments, AR D remains a distressing issue, necessitating further research to improve prevent ion and management strategies.” Funders for this research include European Commission, University of Cyprus. Our news journalists obtained a quote from the research from the University of C yprus, “Moreover, the lack of biomarkers for early quantitative assessment of AR D impedes progress in this area. This study aims to investigate the detection of ARD using intensity-based and novel features of Optical Coherence Tomography (O CT) images, combined with machine learning. Imaging sessions were conducted twic e weekly on twenty-two patients at six neck locations throughout their radiation treatment, with ARD severity graded by an expert oncologist. We compared a trad itional feature-based machine learning technique with a deep learning late-fusio n approach to classify normal skin vs. ARD using a dataset of 1487 images. The d ataset analysis demonstrates that the deep learning approach outperformed tradit ional machine learning, achieving an accuracy of 88%.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting originating from Gujarat , India, by NewsRx correspondents, research stated, “The role of AI in the healt h industry is complex, but in general, it functions like a supercomputer and thi nks like a human.” The news reporters obtained a quote from the research from GMERS Medical College : “Although a few problems need to be addressed to ensure things run well, we ar e confident that they will be fixed quickly and that new AI technologies will qu ickly assist the health-care industry. Policy creation is a comprehensive proces s that includes a detailed analysis of the disease epidemiology, prevalence by r egion, existing diagnostic tools and treatment options, and future action plans to control, eradicate, or eradicate the disease from a nation, a region, or the entire world.” According to the news editors, the research concluded: “AI can be collecting dat a, accurately inputting it, evaluating it, and projecting pandemics or endemics in the future. Health policy creation and the healthcare industry can benefit s ignificantly from using AI techniques.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Urbino, Italy, by NewsRx journalists, research stated, “In the realm of precision medicine, effective pa tient stratification and disease subtyping demand innovative methodologies tailo red for multiomics data. Clustering techniques applied to multi-omics data have become instrumental in identifying distinct subgroups of patients, enabling a f iner-grained understanding of disease variability.” The news correspondents obtained a quote from the research from the University o f Urbino, “Meanwhile, clinical datasets are often small and must be aggregated f rom multiple hospitals. Online data sharing, however, is seen as a significant c hallenge due to privacy concerns, potentially impeding big data’s role in medica l advancements using machine learning. This work establishes a powerful framewor k for advancing precision medicine through unsupervised random forest-based clus tering in combination with federated computing. We introduce a novel multi-omics clustering approach utilizing unsupervised random forests. The unsupervised nat ure of the random forest enables the determination of cluster-specific feature i mportance, unraveling key molecular contributors to distinct patient groups. Our methodology is designed for federated execution, a crucial aspect in the medica l domain where privacy concerns are paramount. We have validated our approach on machine learning benchmark datasets as well as on cancer data from The Cancer G enome Atlas. Our method is competitive with the state-of-the-art in terms of dis ease subtyping, but at the same time substantially improves the cluster interpre tability. Experiments indicate that local clustering performance can be improved through federated computing.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on robotics are presented i n a new report. According to news originating from Dongguan, People’s Republic o f China, by NewsRx correspondents, research stated, “Disassembly line balancing (DLB) is a crucial optimization item in the recycling and remanufacturing of was te products.” Funders for this research include Innovation Team of Intelligent Operation And M aintenance For High-end Equipment; 2022 Postdoctoral Talent Start-up Funding Pro ject. Our news correspondents obtained a quote from the research from Dongguan Univers ity of Technology: “Considering the variations in the number of operators assign ed to each station, this study investigates DLBs with six distinct station confi gurations: single-manned, multi-manned, single-robotic, multi-robotic, single-ma nned-robotic, and multi-manned-robotic setups. First, a unified mixed-integer pr ogramming (MIP) model is established for Type-I DLBs with each configuration to minimize four objectives: the number of stations, the number of operators, the t otal disassembly time, and the idle balancing index. To obtain more solutions, a novel bi-metric is proposed to replace the quadratic idle balancing index and i s used in lexicographic optimization.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news reporting originating from Tor onto, Canada, by NewsRx correspondents, research stated, “Machine learning model s can provide quick and reliable assessments in place of medical practitioners. With over 50 million adults in the United States suffering from osteoarthritis, there is a need for models capable of interpreting musculoskeletal ultrasound im ages.” Financial supporters for this research include Novo Nordisk Health Care Ag. Our news correspondents obtained a quote from the research from University of To ronto: “However, machine learning requires lots of data, which poses significant challenges in medical imaging. Therefore, we explore two strategies for enrichi ng a musculoskeletal ultrasound dataset independent of these limitations: tradit ional augmentation and diffusion-based image synthesis. First, we generate augme nted and synthetic images to enrich our dataset. Then, we compare the images qua litatively and quantitatively, and evaluate their effectiveness in training a de ep learning model for detecting thickened synovium and knee joint recess distens ion. Our results suggest that synthetic images exhibit some anatomical fidelity, diversity, and help a model learn representations consistent with human opinion . In contrast, augmented images may impede model generalizability. Finally, a mo del trained on synthetically enriched data outperforms models trained on un-enri ched and augmented datasets.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting originating from Singapore, Singapore, by NewsRx correspondents, research stated, “Wire Arc Additive Manufa cturing possesses advantages of high deposition rate and low cost compared with other metal additive manufacturing processes. However, potential defects may occ ur during the process, such as pores, cracks, lack of fusion, inclusions, delami nation, and geometrical deviations.” Financial support for this research came from Majestic Rock Resources Pte. Ltd.. Our news editors obtained a quote from the research from Nanyang Technological U niversity, “These defects are undesirable and have negative effects. To optimize the performance of the as-built components, and to reduce the potential defects , a feasible solution is to conduct in-process sensing and provide feedback to t he control system. This article aims to give a comprehensive review of recent pr ogress on sensing technologies, such as optical, acoustic, vision, thermal, and multiple signals-based sensing technologies, and the application of machine lear ning to enhance the ability to extract the needed feedback from the inprocess m onitoring raw data. Effective monitoring of different types of defects typically requires different sensing technologies, focus points, and attentions. Multi- s ensor-based sensing systems may thus be needed to provide full-scale information . These necessities include the need for in-time data fusion and more complex da ta processing.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting out of New Delhi, India, by NewsR x editors, research stated, “Flash floods are one of the most devastating natura l disasters, yet many aspects of their severity and impact are poorly understood .” The news correspondents obtained a quote from the research from Indian Institute of Technology Delhi: “The recession limb is related to post-flood recovery and its impact on communities, yet it remains less documented than the rising limb o f the hydrograph to predict the peak discharge and timing of floods. This work i ntroduces a new metric called the flash flood recovery or recoveriness, which is the potential for recovery of a watershed to pre-flood conditions. Using a comp rehensive database of 78 years and supervised machine learning algorithms, flash flood recovery is mapped in the conterminous United States. A suite of geomorph ological and climatological variables is used as predictors to provide probabili stic estimates of recoveriness. Slope index, river basin area and river length a re found to be the most significant predictors to predict recoveriness.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on artificial intell igence are discussed in a new report. According to news reporting from Renmin Ho spital of Wuhan University by NewsRx journalists, research stated, “Artificial i ntelligence (AI) can acquire characteristics that are not yet known to humans th rough extensive learning, enabling to handle large amounts of pathology image da ta.” Funders for this research include Renmin Hospital of Wuhan University. The news correspondents obtained a quote from the research from Renmin Hospital of Wuhan University: “Divided into machine learning and deep learning, AI has th e advantage of handling large amounts of data and processing image analysis, con sequently it also has a great potential in accurately assessing tumour microenvi ronment (TME) models. With the complex composition of the TME, in-depth study of TME contributes to new ideas for treatment, assessment of patient response to p ostoperative therapy and prognostic prediction. This leads to a review of the de velopment of AI’s application in TME assessment in this study, provides an overv iew of AI techniques applied to medicine, delves into the application of AI in a nalysing the quantitative and spatial location characteristics of various cells (tumour cells, immune and non-immune cells) in the TME, reveals the predictive p rognostic value of TME and provides new ideas for tumour therapy, highlights the great potential for clinical applications.”
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