Development and validation of a novel risk-predicted model for early sepsis-associated acute kidney injury in critically ill patients: a retrospective cohort study by Bo Li, Kun Zhang, Cong-Cong Zhao, Zi-Han Nan, Yan-Ling Yin, Li-Xia Liu, Zhen-Jie Hu

“…The least absolute shrinkage and selection operator regression method was used to screen the risk factors, and the final screened risk factors were constructed into four machine learning models to determine an optimal model. External validation was performed using another single-centre intensive care unit (ICU) database.Setting Data for the development cohort were obtained from the MIMIC-IV 2.0 database, which is a large publicly available database that contains information on patients admitted to the ICUs of Beth Israel Deaconess Medical Center in Boston, Massachusetts, USA, from 2008 to 2019. …”
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A land-cover-assisted super-resolution model for retrospective reconstruction of MODIS-like NDVI data across the continental United States by blending Landcover300m and GIMMS NDVI3... by Zhicheng Zhang, Zhenhua Xiong, Xuewen Zhou, Kun Xiao, Wei Wu, Qinchuan Xin

“…This study introduces a novel deep learning-based model, termed the Land-Cover-assisted Super-Resolution SpatioTemporal Fusion model (LCSRSTF), designed to produce biweekly 500-meter MODIS-like data spanning from 1992 to 2010 across the Continental United States (CONUS). …”
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Comprehensive approach to predictive analysis and anomaly detection for road crash fatalities by Chopparapu Gowthami, S. Kavitha

“…The research offers policymakers, transportation authorities, and safety advocates practical insights by utilizing sophisticated machine-learning algorithms and integrating multiple datasets. …”
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Comparison of new secondgeneration H1 receptor blockers with some molecules; a study involving DFT, molecular docking, ADMET, biological target and activity by Velid Unsal, Erkan Oner, Reşit Yıldız, Başak Doğru Mert

“…This study demonstrated the potential of machine learning methods in understanding and discovering H1 receptor blockers. …”
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Knowledge Management System Berbasis Web tentang Budidaya Hidroponik untuk Mendukung Smart Society by Ariq Cahya Wardhana, Yani Nurhadryani, Sri Wahjuni

“…Facilitate access to digital learning facilities as an essential part of the plan of the Bogor City government, namely smart society, information technology support is needed as a means of sharing hydroponic cultivation knowledge. …”
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Pengembangan Soal Pemecahan Masalah untuk Siswa Sekolah Menengah Pertama Menggunakan Pendekatan Pendidikan Matematika Realistik Indonesia by Ichdar Domu, Susi Aryani Manangin, Kinzie Feliciano Pinontoan

“…Validity is obtained based on expert validation, while practicality is since the prototype of the questions developed can be used properly by students, In addition, the prototype questions developed have the potential effect to improve students' mathematical thinking and stimulate students' enthusiasm for learning. There are 80.1% of students who use various problem-solving strategies in solving the existing prototype questions.…”
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Behaviors and influencing factors of Chinese oncology nurses towards frailty care: A cross-sectional study based on knowledge-attitude-practice theory in 2024. by Xiaoxue Chen, Fang Xiao, Yuhua Miao, Huiying Qin, Lirong Yang, Fang Shen, Xiuhong Yuan

“…Pearson's correlations analysis showed that nursing grades (r = 0.13), frailty-related training willingness (r = 0.18), nursing frail patients experience (r = 0.22), frailty-related knowledge learning experience (r = 0.33), frailty-related training experience (r = 0.17), frailty care knowledge (r = 0.23), and hospice care attitudes (r = 0.54) were positively associated with frailty care behaviors. …”
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Research on Risk Prediction of Condiments Based on Gray Correlation Analysis – Deep Neural Networks by Miao Zhang, Yiran Wan, Haiyang He, Yuanjia Hu, Changhong Zhang, Jingyuan Nie, Yanlei Wu, Kaiying Deng, Xun Lei, Xianliang Huang

“…Then, three machine learning models, Deep Neural Network (DNN), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost), were used to predict the comprehensive risk values. …”
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Refining management strategies for Lennox–Gastaut syndrome: Updated algorithms and practical approaches by Stéphane Auvin, Alexis Arzimanoglou, Mercè Falip, Pasquale Striano, J. Helen Cross

“…Most people with LGS have learning difficulties and need a lot of support, often in residential care. …”
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A Comparison of Classification Algorithms for Predicting Dis-tinctive Characteristics in Fine Aroma Cocoa Flowers Using WE-KA Modeler by Daniel Tineo, Yuriko S. Murillo, Mercedes Marín, Darwin Gomez, Victor H. Taboada, Malluri Goñas, Lenin Quiñones Huatangari

“…This research provides a comprehensive overview of the use of machine learning to analyze functional traits of flowers that most influence cocoa genetic diversity. …”
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Antin-diabetic cognitive dysfunction effects and underpinning mechanisms of phytogenic bioactive peptides: a review by Xiaoli Liu, Xiaoli Liu, Shenglian Mao, Shenglian Mao, Yuxue Yuan, Yuxue Yuan, Zilin Wang, Zilin Wang, Yang Tian, Yang Tian, Yang Tian, Liang Tao, Liang Tao, Jiahe Dai, Jiahe Dai

“…Diabetic cognitive dysfunction is one of the important comorbidities and complications of diabetes, which is mainly manifested by loss of learning ability and memory, behavioural disorders, and may even develop into dementia. …”
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An Analysis of the Vocational-Educational Problematics for Substantiating Production Specialist Competencies by V. E. Steinberg, L. V. Vakhidova, E. M. Gabitova

“…This also enables to effectively build and timely adjust the learning process of really demanded, competitive experts capable to realise innovative projects, to master and create new equipment, i. e. to keep the successful operation and development of production and economics of a region and a country in general. …”
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ECG-LM: Understanding Electrocardiogram with a Large Language Model by Kai Yang, Massimo Hong, Jiahuan Zhang, Yizhen Luo, Suyuan Zhao, Ou Zhang, Xiaomao Yu, Jiawen Zhou, Liuqing Yang, Ping Zhang, Mu Qiao, Zaiqing Nie

“…However, the interpretation of ECG data alongside patient information demands substantial medical expertise and resources. While deep learning methods help streamline this process, they often fall short in integrating patient data with ECG readings and do not provide the nuanced clinical suggestions and insights necessary for accurate diagnosis. …”
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Spatiotemporal Variation and Driving Factors of Carbon Sequestration Rate in Terrestrial Ecosystems of Ningxia, China by Yi Zhang, Chunxiao Cheng, Zhihui Wang, Hongxin Hai, Lulu Miao

“…Based on ground observation data and multimodal datasets, the optimal machine learning model (EXT) was used to invert a 30 m high-resolution vegetation and soil carbon density dataset for Ningxia from 2000 to 2023. …”
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A multi-stakeholder collaborative approach to awareness, education and support needed in the haemophilia gene therapy patient journey – a report on insights from a European patient... by O’Mahony Brian, Fletcher Simon, Baarslag Manuel, Khair Kate, Breederveld Daan, Jansen Nathalie, Pembroke Luke, Pinachyan Karen, Sivasubramaniyam Sujan

“…Teach-back could help ensure appropriate levels of understanding; psychological support could aid managing expectations. Peer-to-peer learning delivered across a variety of platforms, to share experiences of gene therapy and contextualise more ‘formal’ gene therapy education, was considered invaluable.…”
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Generative spatial artificial intelligence for sustainable smart cities: A pioneering large flow model for urban digital twin by Jeffrey Huang, Simon Elias Bibri, Paul Keel

“…It is specifically tailored for integration into UDT systems to enhance predictive analytics, adaptive learning, and complex data management functionalities. …”
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The Double-Edged Sword of Third-Party Resources: Examining Use and Financial Burden of Extracurricular Tools in Medical Students [version 2; peer review: 1 approved, 2 approved wit... by Dimitrios Papanagnou, Saaniya Farhan, Andres Fernandez, Meryem Guler, Drake Kienzle, Faizaan Siddique

“…Transition to virtual learning in 2020 fostered a greater reliance on these online third-party resources (i.e., educational tools distinct from formal medical curriculum), yet existing literature have rarely evaluated their efficacy. …”
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Synaptic transistor implementing potentiation or depression via field distribution modulation of dual dielectric layers by single-polarity pulsed voltage stimuli by Jieun Kim, Jung Wook Lim, Chohyeon Park, Chaerin Yu, Jaehee Lee

“…This study designs, fabricates, and characterizes a dual-gate dielectric synaptic device that utilizes interfacial charge traps to mimic long-term potentiation (LTP) and long-term depression (LTD), which are essential for learning and memory. The device is fabricated using a standard complementary metal-oxide-semiconductor process and is composed of a TiO2 channel deposited over a dual dielectric of SiOx on Al2O3. …”
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Development of a metabolome-based respiratory infection prognostic during COVID-19 arrival by John I. Robinson, Laura R. Marks, Andrew L. Hinton, Jane A. O'Halloran, Charles W. Goss, Peter J. Mucha, Jeffrey P. Henderson

“…We obtained LC-MS profiles in the initial cohort and used machine learning methods to define a simplified urine metabolomic signature associated with respiratory failure or death by 90 days. …”
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Urine proteomics defines an immune checkpoint-associated nephritis signature by Cassian Yee, Jamie S Lin, James P Long, Shailbala Singh, Yanlan Dong

“…Using statistical and machine learning methods, we constructed a novel urine biomarker signature—IL-5+Fas—that achieved an area under the curve of 0.94 for diagnosing ICI-AIN.By leveraging high-sensitivity proteomics, we developed a non-invasive strategy for diagnosing ICI-AIN. …”
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