Rapid Disaster Data Dissemination and Vulnerability Assessment through Synthesis of a Web-Based Extreme Event Viewer and Deep Learning by P. Shane Crawford, Mohammad A. Al-Zarrad, Andrew J. Graettinger, Alexander M. Hainen, Edward Back, Lawrence Powell

“…The methods establish a baseline of preevent infrastructure functionality that can be used to measure impacts and temporal recovery following a disaster. …”
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Geospatial Robust Wheat Yield Prediction Using Machine Learning and Integrated Crop Growth Model and Time-Series Satellite Data by Rana Ahmad Faraz Ishaq, Guanhua Zhou, Guifei Jing, Syed Roshaan Ali Shah, Aamir Ali, Muhammad Imran, Hongzhi Jiang, Obaid-ur-Rehman

“…Crop traits, which historically capture the cumulative effect of these factors, exhibit functional relationships critical for optimizing productivity. …”
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The development of an attention mechanism enhanced deep learning model and its application for body composition assessment with L3 CT images by Liang Zhang, Jiao Li, Zhi Yang, Jun Yan, Lin Zhang, Long-bo Gong

“…An internet-based application was developed using L3BCSM, which has four functional modules: population analysis, time series analysis, consistency analysis, and manual result checking. …”
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Does model type influence the effectiveness of combined action observation and motor imagery training for novices learning an Ankle Pick takedown? by Samantha Chye, Ashika Chembila Valappil, Ryan Knight, Andrew Greene, David Shearer, Cornelia Frank, Ceri Diss, Adam Bruton, Adam Bruton

“…Both the AOMIOTHER and Control conditions led to improved functional changes in mental representation structures while the structures for the AOMISELF condition became less similar to the reference structure over time.DiscussionCollectively, the largely null findings (n = 13, 92.86%) suggest that physical practice has the strongest influence on motor adaptations for this complex motor skill at these early stages of learning. …”
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A tumor-infiltrating B lymphocytes -related index based on machine-learning predicts prognosis and immunotherapy response in lung adenocarcinoma by Jiale Fang, Siyuan Yu, Wei Wang, Wei Wang, Cheng Liu, Xiaojia Lv, Jiaqi Jin, Xiaomin Han, Xiaomin Han, Xiaomin Han, Fang Zhou, Yukun Wang

“…A comprehensive machine learning approach, utilizing ten distinct algorithms, facilitated the creation of a TILB-related index (BRI) across the TCGA, GSE31210, and GSE72094 datasets. …”
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Identification of anoikis-related genes classification patterns and immune infiltration characterization in chronic rhinosinusitis with nasal polyps based on machine learning by Ziqi Chen, Lingmei Qu, Qing Hao, Shuang Teng, Shuo Liu, Qin Wu, Hongtian Yi, Xianji Shen, Liang Li, Zhaonan Xu, Yanan Sun

“…Functional annotation was performed based on Gene Ontology (GO) terms, and pathway enrichment analysis was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. …”
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Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods by Ankita Lawarde, Ankita Lawarde, Masuma Khatun, Prakash Lingasamy, Prakash Lingasamy, Andres Salumets, Andres Salumets, Andres Salumets, Vijayachitra Modhukur, Vijayachitra Modhukur

“…Despite their established influence on tumor progression and therapeutic resistance, the application of miRNA interaction networks for tumor tissue-of-origin (TOO) classification remains underexplored.MethodsWe developed a machine learning (ML) framework that integrates miRNA-mRNA-lncRNA interaction networks to classify tumors by their tissue of origin. …”
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Fourier Features and Machine Learning for Contour Profile Inspection in CNC Milling Parts: A Novel Intelligent Inspection Method (NIIM) by Manuel Meraz Méndez, Juan A. Ramírez Quintana, Elva Lilia Reynoso Jardón, Manuel Nandayapa, Osslan Osiris Vergara Villegas

“…Form deviation generated during the milling profile process challenges the precision and functionality of industrial fixtures and product manufacturing across various sectors. …”
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Identification of novel molecular subtypes and construction of a prognostic signature via multi-omics analysis and machine learning in lung adenocarcinoma by Ke Ma, Jie Xu, Jie Xu, Congyue Wang, Congyue Wang, Xu Cao, Xu Cao, Wenjie Yu, Jingjing Xi, Xuan Zhang, Jiamin Zhan, Yang Liu, Aoyang Yu, Aoyang Yu, Shuhan Liu, Yanhua Liu, Yanhua Liu, Chong Chen, Chong Chen, Xiaoli Mai, Xiaoli Mai

“…A multi-omics and machine learning-driven prognostic signature (MO-MLPS) was constructed in The Cancer Genome Atlas (TCGA) LUAD dataset using ten machine learning algorithms and subsequently validated across six independent datasets from the Gene Expression Omnibus (GEO) database. …”
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Exploring Mortality and Prognostic Factors of Heart Failure with In-Hospital and Emergency Patients by Electronic Medical Records: A Machine Learning Approach by Yu CS, Wu JL, Shih CM, Chiu KL, Chen YD, Chang TH

“…After a series of data pre-processing in the electronic medical record system, several machine learning models were used to evaluate predictions of HF mortality. …”
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Development of a prediction model for acute respiratory distress syndrome in ICU patients with acute pancreatitis based on machine learning algorithms by REN Xia*，LIU Luojie，ZHA Junjie，YE Ye，XU Xiaodan，YE Hongwei，ZHANG Yan

“…Demographic characteristics，initial vital signs，laboratory data，functional scores，and complications within the initial 24⁃hour of ICU admission were collected. …”
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Novel post-translational modification learning signature reveals B4GALT2 as an immune exclusion regulator in lung adenocarcinoma by Ge Zhang, Zhenfa Zhang, Lianmin Zhang, Guangyao Zhou, Pengpeng Zhang, Dingli Wang, Shuai Jiang

“…While post-translational modifications are known to influence tumor progression, their prognostic value in LUAD remains largely unexplored.Methods We developed a post-translational modification learning signature (PTMLS) using machine learning techniques, analyzing data from 1231 LUAD patients across seven global cohorts. …”
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Evaluation on nature-connected environment in building embedded landscape: theory, detection, and case design by Shu Zhong, Jiao Ren

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Children who screen positive for autism at 2.5 years and receive early intervention: a prospective naturalistic 2-year outcome study by Spjut Jansson B, Miniscalco C, Westerlund J, Kantzer A, Fernell E, Gillberg C

“…Keywords: autism spectrum disorder, preschool children, early intervention, ABA, cognitive function, follow-up…”
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The study of the effect of virtual reality technology combined with sports games on improving cognitive function in patients with brain injury: a meta analysis of randomized contro... by Yuze Zhang, Yuze Zhang, Haojie Li, Hong Xiao

“…These results support virtual reality as an effective cognitive intervention for brain-injured patients.ConclusionVirtual reality (VR) sports games significantly enhanced cognitive function, coordination, and reaction speed in brain-injured patients, thereby boosting their learning motivation and engagement.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024581533.…”
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Resepsi Fungsional Surah Al-Fātiḥaḥ di Kalangan Disabilitas Sensorik Rungu Wicara Rumah Qur’an Sahabat Tuli Asy-Syukur Kediri by Faricha Cahya Fajrianti, Kholila Mukaromah

“…This article aims to understand more deeply how surah Al-Fātiḥaḥ is perceived and functioned practically by people with hearing and speech sensory disabilities (PDSRW) at the Qur'an House of the Deaf Friends Asy-Syukur Kediri. …”
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Effectiveness of predictive scoring systems in predicting mortality in relation to baseline kidney function in adult intensive care unit patients: a systematic review protocol by Greg Knoll, Ayub Akbari, Risa Shorr, Edward G Clark, Gregory L Hundemer, Amos Buh, Hajar El Wadia, Abdulghani Omar Kabli, Marisha Karim, Nandini Biyani, Inok Lee

“…By excluding randomised trials, paediatric studies, case reports and machine learning-derived models, this review focuses on the direct practical use of the scoring systems in adult ICU patients. …”
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Long-Term (2015–2024) Daily PM_2.5 Estimation in China by Using XGBoost Combining Empirical Orthogonal Function Decomposition by Jiacheng Jiang, Jiaxin Dong, Yu Ding, Wenjia Ni, Jie Yang, Siwei Li

“…Then, a novel approach by integrating XGBoost with EOF (Empirical Orthogonal Function) decomposition is introduced for PM_2.5 estimation. …”
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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

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Unraveling progressive verbal memory deficits in Huntington’s disease: insights from the LASSI-L by Luis A. Sierra, Japleen Kaur, Samuel A. Frank, Samuel A. Frank, Mark A. Halko, Mark A. Halko, Rosie E. Curiel Cid, David A. Loewenstein, Jody Corey-Bloom, Simon Laganiere, Simon Laganiere

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