Improving prediction accuracy of hospital arrival vital signs using a multi-output machine learning model: a retrospective study of JSAS-registry data by Yasuyuki Kawai, Koji Yamamoto, Keisuke Tsuruta, Keita Miyazaki, Hideki Asai, Hidetada Fukushima

“…Abstract Background Critically ill patients can deteriorate rapidly; therefore, prompt prehospital interventions and seamless transition to in-hospital care upon arrival are crucial for improving survival. …”
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Nurses’ perception of patient safety culture using the Hospital Survey on Patient Safety Culture tool and its association with nursing-patient outcomes: a systematic review in Iran... by Alireza Hajizadeh, Behrouz Amini Kordkandi, Sevda Sadeghpour, Milad Khodavandi, Jalal Saeidpour, Edris Kakemam

“…Further research is warranted to identify and evaluate specific interventions that effectively improve PSC and associated outcomes.…”
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Integration of UAV Multispectral Remote Sensing and Random Forest for Full-Growth Stage Monitoring of Wheat Dynamics by Donghui Zhang, Hao Qi, Xiaorui Guo, Haifang Sun, Jianan Min, Si Li, Liang Hou, Liangjie Lv

“…The random forest model exhibited superior predictive accuracy, with a mean squared error (MSE) significantly lower than that of traditional regression models, particularly during the flowering and ripening stages, where the prediction error for plant height was less than 1.01 cm. …”
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Overview of Effects of Motor Learning Strategies in Neurologic and Geriatric Populations: A Systematic Mapping Review by Li-Juan Jie, PhD, Melanie Kleynen, PhD, Guus Rothuizen, MSc, Elmar Kal, PhD, Andreas Rothgangel, PhD, Susy Braun, PhD

“…Two reviewers extracted descriptive data regarding the population, type of motor learning strategy/intervention, frequency and total duration intervention, task trained, movement performance measures, assessment time points, and between-group effects of the included studies. …”
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Effect of group-based nutritional education combined with individual standard care for outpatients with type 2 diabetes: study protocol for a randomized clinical trial {1} by Aline Busanello, Vanessa Machado Menezes, Olivia Garbin Koller, Ândria Völz Andreia, Jussara Carnevale de Almeida

“…Sample size calculations were based on an estimated mean difference of 0.59 ± 1.39% in HbA1c with the intervention (patient-centered group), using a type I error rate of 5% and a type II error rate of 20%. …”
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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials by Simin Nazari, Amira Abdelrasoul

“…Researchers often rely on trial-and-error approaches to enhance membrane hemocompatibility by reducing these interactions. …”
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Unveiling construction accident causation: a scientometric analysis and qualitative review of research trends by Haoyu Zang, Ming Li, Zhiyao Jin, Jingfei Huang

“…These incidents arise from interlinked causal factors, including human error, management shortcomings, technical failures, and environmental conditions. …”
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The Automatable Activity–Based Approach to Complexity Unit Scoring as a task-specific model approach to monetizing outcomes of pathology artificial intelligence solutions by Stavros Pantelakos, Martha Nifora, Georgios Agrogiannis

“…In this context, the need for monetization of digital health interventions has been recently emphasized. Previous studies have attempted to extrapolate cost containment in conjunction with the implementation of digital pathology solutions mostly on the basis of operational cost savings or diagnostic error reduction. …”
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Characterization of 3-Hydroxyisobutyryl-Coa Hydrolase (HIBCH) Deficiency in Bahrain: A Retrospective Cohort Study by Emtithal Al jishi, Zahra Al sahlawi, Huda Omran, Mohammed S. Almaliki, Faten Al mahroos, Heba Alkoheji

“…Background: 3-Hydroxyisobutyryl-CoA hydrolase (HIBCH) deficiency is a rare inborn error of valine catabolism associated with progressive neurological impairment. …”
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Health facility readiness and facility-based birth in Haiti: a maximum likelihood approach to linking household and facility data by Christopher G Kemp, Reed Sorensen, Nancy Puttkammer, Reynold Grand’Pierre, Jean Guy Honoré, Lauren Lipira, Christopher Adolph

“…Our model estimated that rural facilities (bandwidth (h)=12.28, standard error (SE)=0.16) spread their readiness over larger areas than urban facilities (h=7.14, SE=0.016). …”
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Predicting medication wastage using machine learning based on patient beliefs by Firdaus Aziz, Sorayya Malek, Shubathira Sooriamoorthy, Ilham Asyilah Mahamood, Chong Wei Wen, Sharifah M. Syed Ahmad, Putri Nur Fatin Amir Rudin, Adliah Mhd Ali

“…Multiple ML regression models were evaluated to predict medication wastage, with performance assessed based on root mean squared error (RMSE). Results The XGBoost model achieved the best performance with the lowest RMSE of 4.67, outperforming other models (RMSE range:4.68–5.10). …”
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Built environment characteristics and driving speed in 30 km/h zones: a Dutch national analysis by Paul Schepers, Werner van Loo, Wouter Mieras, Hans Drolenga, Dick de Waard, Marco Helbich

“…Out study provides valuable insights into the effectiveness of speed-reduction measures, offering guidance for interventions targeting streets with excessive speeds. …”
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NH4 Modelling with ARIMA and LSTM by Hanna Arini Parhusip, Suryasatriya Trihandaru, Johanes Dian Kurniawan

“…Despite its use, ARIMA's Root Mean Square Error (RMSE) performance was found lacking compared to more advanced methods. …”
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Modeling the distribution and progression of motor ability among children with cerebral palsy: An analysis of three reference centile sets by Rachel Sanderlin, Charlotte Schluger, Joe Wu, Francis Ang Eusebio, Amy L. Roberts, Laura Prosser

“…Prediction errors increased at younger ages and higher motor ability. …”
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Indoor Group Identification and Localization Using Privacy-Preserving Edge Computing Distributed Camera Network by Chaitra Hegde, Yashar Kiarashi, Amy D. Rodriguez, Allan I. Levey, Matthew Doiron, Hyeokhyen Kwon, Gari D. Clifford

“…Our group identification method demonstrated an F1 score of up to 90% with a mean absolute error of 1.25 m for group localization on our benchmark dataset. …”
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A Cross-Cultural Validation of the Italian Version of the Nurse’s Environmental Awareness Tool (NEAT) by Alessio Conti, Marco Clari, Eleonora Italia, Chiara Gasparini, Beatrice Albanesi, Franco Cirio, Giancarlo Mercurio, Sara Campagna, Valerio Dimonte

“…The Italian version of the NEAT is designed for screening purposes, guiding educational interventions, and supporting research in both clinical and academic contexts. …”
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Continuous Estimation of Cardiac Output in Critical Care: A Noninvasive Method Based on Pulse Wave Transit Time Compared with Transpulmonary Thermodilution by Ulrike Ehlers, Rolf Erlebach, Giovanna Brandi, Federica Stretti, Richard Valek, Stephanie Klinzing, Reto Schuepbach

“…Estimation of cardiac output (CO) and evaluation of change in CO as a result of therapeutic interventions are essential in critical care medicine. …”
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Navigating uncertainty in environmental DNA detection of a nuisance marine macroalga. by Patrick K Nichols, Kaʻuaʻoa M S Fraiola, Alison R Sherwood, Brian B Hauk, Keolohilani H Lopes, Colt A Davis, James T Fumo, Chelsie W W Counsell, Taylor M Williams, Heather L Spalding, Peter B Marko

“…However, eDNA analyses are prone to errors that can complicate their use in management frameworks. …”
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Psychometric evaluation of the Persian version of the adult chronic kidney disease self-management instrument in the Iranian population by Simin Alasvand, Mehrnaz Ahmadi, Hamid Sharif-Nia, Marziyeh Asadizaker

“…The absolute reliability, as determined by Standard Error of Measurement results, was 3.16. Additionally, the Minimum Detectable Change was estimated to be 8.75. …”
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A System Dynamics Approach to Corn Production in indonesia: Causal Loop Diagram by Asriani Asriani, Dhian Herdhiansyah

“…Model verification was conducted using the Mean Absolute Percentage Error (MAPE) method, and simulations were performed with Powersim software to project future outcomes. …”
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