Meso Hybridized Silk Fibroin Watchband for Wearable Biopotential Sensing and AI Gesture Signaling by Xiao Wang, Changsheng Lu, Zerong Jiang, Guangwei Shao, Jingzhe Cao, Xiang Yang Liu

“…Through smart raining via deep learning, we achieved an unparalleled recognition rate (96% across 20 volunteers of different genders) among other EMG sensing devices. …”
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Automatic Comparative Chest Radiography Using Deep Neural Networks by Redwan Sony, Carolyn V. Isaac, Alexis Vanbaarle, Clara J. Devota, Todd Fenton, Joseph T. Hefner, Arun Ross

“…We then explored three families of deep neural networks, each selected for its unique strengths in addressing specific challenges in deep learning for processing these ROIs as well as the entire radiograph. …”
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HFIFNet: Hierarchical Feature Interaction Network With Multiscale Fusion for Change Detection by Mingzhi Han, Tao Xu, Qingjie Liu, Xiaohui Yang, Jing Wang, Jiaqi Kong

“…Benefiting from deep learning, numerous methods have achieved significant results in the CD of clearly changed targets. …”
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Representing and Quantifying Conformational Changes of Kinases and Phosphatases Using the TSR-Based Algorithm by Tarikul I. Milon, Krishna Rauniyar, Sara Furman, Khairum H. Orthi, Yingchun Wang, Vijay Raghavan, Wu Xu

“…TSR keys are effective when used as features for unsupervised machine learning and for key searches. If discriminative TSR keys are identified, they can be mapped back to atomic details within the amino acids involved. …”
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Dual‐fluorescence imaging and automated trophallaxis detection for studying multi‐nutrient regulation in superorganisms by Lior Baltiansky, Einav Sarafian‐Tamam, Efrat Greenwald, Ofer Feinerman

“…Additionally, our image‐based deep learning algorithm for automatic detection of ant trophallaxis events efficiently yields a detailed record of all food‐transfer interactions. …”
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A graph neural network approach for hierarchical mapping of breast cancer protein communities by Xiao Zhang, Qian Liu

“…Existing approaches are subjective and fail to take information from protein sequences into consideration. Deep learning can automatically learn features from protein sequences and protein–protein interactions for hierarchical clustering. …”
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Reflection to enhance dental students´ awareness of and comfort with uncertainty – an experimental study by Joséphine Brodén, Helena Fransson, Niklas Vareman, Maria Pigg

“…The exercises and questionnaire were administered in mandatory sessions on an internet-based learning platform, ensuring anonymity and informed consent. …”
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Lithuanian Language at School: Scientific Insights and Pedagogical Experience by Ona Laima Gudzinevičiūtė, Džiuljeta Maskuliūnienė

“…The field of topics is broad, discussions include: general language, dialects, language norming, language in the digital space, language didactics, the process of language teaching and learning, and the effects of bilingualism. The articles in the literature section are divided into five thematic blocks: 1) Promotion of reading, professional press for teachers; 2) Lithuanian writers’ works in school, concerns of reading classics; 3) Children’s literature and school; 4) Working with the text to prepare the future reader; 5) Non-traditional literature teaching methods and other problems. …”
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Leg og det legende i højere uddannelse? – En legekvalitetsanalyse af 36 didaktiske designs på pædagog- og læreruddannelsen by Helle Marie Skovbjerg, Helle Hovgaard Jørgensen

“…The main contribution of this paper is to demonstrate the usefulness of the concept of play qualities in developing playful approaches to learning in higher education.  …”
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Evidence from NHANES 2011–2014: a correlation between the weight-adjusted-waist index and cognitive abilities in the United States by Chan Zhao, Xintian Xu, Chunyan Hao

“…Three cognitive assessments were administered: the Animal Fluency Test (AFT), the Digit Symbol Substitution Test (DSST), and the Word Learning and Recall Module from the Coalition to Establish a Registry for Alzheimer’s Disease (CERAD). …”
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Large language models improve the identification of emergency department visits for symptomatic kidney stones by Cosmin A. Bejan, Amy M. Reed, Matthew Mikula, Siwei Zhang, Yaomin Xu, Daniel Fabbri, Peter J. Embí, Ryan S. Hsi

“…In this study, we investigated the abilities of multiple LLMs and traditional machine learning models to analyze emergency department (ED) reports and determine if the corresponding visits were due to symptomatic kidney stones. …”
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What can qualitative research do for randomised controlled trials? A systematic mapping review by J Hewison, A O'Cathain, A Rudolph, K J THOMAS, S J Drabble

“…Researchers can increase the impact of this work on trials by undertaking more of it at the pretrial stage and being explicit within their articles about the learning for trials and evidence-based practice.…”
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Neural Determinants of Sedentary Lifestyle in Older Adults: A Brain Network Analysis by Mohsen Bahrami, Jonathan H Burdette, Paul J Laurienti, Barbara J Nicklas, W Jack Rejeski, Jason Fanning

“…Method The goal of the current study, using baseline fMRI and accelerometry data from 36 participants and advanced machine learning tools, was to determine if we could identify complex brain circuits underlying variability associated with changes in sitting time and daily steps during the 6‐month intensive phase among participants randomized to the WL + SitLess treatment condition. …”
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Myoelectric pattern recognition with virtual reality and serious gaming improves upper limb function in chronic stroke: a single case experimental design study by Maria Munoz-Novoa, Morten B. Kristoffersen, Katharina S. Sunnerhagen, Autumn Naber, Max Ortiz-Catalan, Margit Alt Murphy

“…Abstract Background Myoelectric pattern recognition (MPR) combines multiple surface electromyography channels with a machine learning algorithm to decode motor intention with an aim to enhance upper limb function after stroke. …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction.…”
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Anomaly Detection Using Explainable Random Forest for the Prediction of Undesirable Events in Oil Wells by Nida Aslam, Irfan Ullah Khan, Aisha Alansari, Marah Alrammah, Atheer Alghwairy, Rahaf Alqahtani, Razan Alqahtani, Maryam Almushikes, Mohammed AL Hashim

“…Additionally, it can lead to several faulty events that could increase costs and production losses since the engineers tend to focus on the analysis rather than detecting the faulty events. Recently, machine learning (ML) techniques have significantly solved enormous real-time data anomaly problems by decreasing the data engineers’ interaction processes. …”
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Functional Brain Correlates of Upper Limb Spasticity and Its Mitigation following Rehabilitation in Chronic Stroke Survivors by Svetlana Pundik, Adam D. Falchook, Jessica McCabe, Krisanne Litinas, Janis J. Daly

“…Methods. 23 stroke survivors (>6 months) were treated with an arm motor learning and spasticity therapy (5 d/wk for 12 weeks). …”
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Research on new energy power plant network traffic anomaly detection method based on EMD by Danni Liu, Shengda Wang, YutongLi, Ji Du, Jia Li

“…The incorporation of these state-of-the-art convolutional methods into the CNN-GRU model enhances detection capabilities and opens up new avenues for exploration in the realm of anomaly detection based on deep learning. Results The grid deployment of large-scale PV power facilities relies heavily on dependable communication networks. …”
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Multi-omics analysis reveals the sensitivity of immunotherapy for unresectable non-small cell lung cancer by Rui Wu, Kunchen Wei, Xingshuai Huang, Yinge Zhou, Xiao Feng, Xin Dong, Hao Tang

“…Finally, potential biomarkers were picked out by applying machine learning methods including random forest and stepwise regression and prediction models were constructed by logistic regression.ResultsThe presence of metabolites and proteins in peripheral blood plasma was causally associated with both non-small cell lung cancer and PD-L1/PD-1 expression levels. …”
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MicroRNA-155 modulates methotrexate-induced spatial memory impairment by disruption of the blood-brain barrier integrity by Yu-Chieh Chen, Li-Tung Huang, Hong-Ren Yu, Jiunn-Ming Sheen

“…Besides, IP MTX resulted in impaired learning acquisition, which can be reversed by anti-miR155 treatment. …”
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