Co-designing a dashboard of predictive analytics and decision support to drive care quality and client outcomes in aged care: a mixed-method study protocol by Andrew Georgiou, Julie Ratcliffe, Jeffrey Braithwaite, Kristiana Ludlow, Johanna Westbrook, Joyce Siette, Jacqueline Close, Stephen R Lord, Melissa T Baysari, Wu Yi Zheng, Richard O Day, Amy Nguyen, Mikaela Jorgensen, Melissa Miao, Magdalena Z Raban, Karla Seaman, Elizabeth Beattie, Deborah Debono, Leonard C Gray, Cynthia Stanton, Alex Thompson, Kimberly E Lind, David Roffe, Jo Root, Libby O’Toole, Marcela Carrasco, Javed Shaikh, Jeffrey Wong, Rebecca Haddock

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Early prediction value of ASL-MRI for induced chemotherapy response and short-term efficacy of locally advanced nasopharyngeal carcinoma by SHEN Mingjun, YANG Chaolin, ZHOU Ziyan, WANG Rensheng, KANG Min

“…Methods Thirty-eight newly diagnosed LA-NPC patients were enrolled. …”
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Evaluation and estimation of changes in water quality using zoning map and researchers-developed software (case study: Pir-Bazar river) by Majid Homami, Seyed Ahmad Mirbagheri, Seyed Mehdi Borghei, Madjid Abbaspour

“…Materials and methods: The present study aimed at evaluating the eutrophication status and prediction of temporal-spatial changes in nutrients concentrations, such as ammonium-nitrogen (N-NH3), nitrate (N-NO3), total nitrogen (TN), phosphorous (PO4-3), TP, in the estuary of Pir-Bazar river as the main and most important stream feeding the Anzali International Wetland. …”
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Evaluating climatic variability's impact on milk yield across climate zones: A machine learning-based comparative study of Switzerland and Thailand by Boonyarat Phadermrod, Varunya Attasena

“…However, differences in datasets and modeling methods hinder direct comparisons. This study systematically compares conventional and modern machine learning models for milk yield prediction and evaluates the influence of climatic variability in Switzerland (moderate climate) and Thailand (tropical climate) using the same analytical framework.Five models—linear regression, ridge regression, gradient boosting regression, AdaBoost, and LightGBM—are tested with various feature sets, including Day-in-Milk, individual and combined meteorological variables, and three lagged milk yield values to assess their predictive value. …”
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Synthetic Data Generation and Evaluation Techniques for Classifiers in Data Starved Medical Applications by Wan D. Bae, Shayma Alkobaisi, Matthew Horak, Siddheshwari Bankar, Sartaj Bhuvaji, Sungroul Kim, Choon-Sik Park

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Correlation analysis and recurrence evaluation system for patients with recurrent hepatolithiasis: a multicentre retrospective study by Zihan Li, Zihan Li, Yibo Zhang, Zixiang Chen, Jiangming Chen, Hui Hou, Cheng Wang, Zheng Lu, Xiaoming Wang, Xiaoping Geng, Fubao Liu

“…Nine predictive models, which we named the Correlation Analysis and Recurrence Evaluation System (CARES), were developed and compared using machine learning (ML) methods to predict the patients’ dynamic recurrence risk within 5 post-operative years. …”
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Impact of pulse pressure variability evaluated by visit-to-visit on heart failure events in patients with hypertension: insights from the SPRINT trial by Huan Ma, Minyan Wang, Chu Qin, Oscar Onayi Mandizadza, Li Wu, Ruichen Cong, Yun Shi, Wei Mao, Conghua Ji

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Computational evaluation on spectroscopic (FT-IR, Raman), electronic and biological, and NLO properties of cirsilineol by DFT, ADMET, and molecular docking method by Tirth Raj Paneru, Poonam Tandon, Bhawani Datt Joshi

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Computational evaluation on spectroscopic (FT-IR, Raman), electronic and biological, and NLO properties of cirsilineol by DFT, ADMET, and molecular docking method by Tirth Raj Paneru, Poonam Tandon, Bhawani Datt Joshi

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Evaluation of the Effect of Uncertainties on the Acoustic Behavior of a Porous Material Located in a Duct Element Using the Monte Carlo Method by Hanen Hannachi, Hassen Trabelsi, Marwa Kani, Mohamed Taktak, Mabrouk Chaabane, Mohamed Haddar

“…In the present study, this method is applied to a theoretical model predicting the acoustic behavior of a porous material located in a duct element to evaluate the impact of each input error on the computation of the acoustic proprieties such as the reflection and transmission coefficients as well as the acoustic power attenuation and the transmission loss of the studied element. …”
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Maximal mouth opening is a simple method to evaluate the treatment outcome of temporomandibular joint arthritis in patients with juvenile idiopathic arthritis by Mia Huhtanen, Katriina Mikola, Anu Kiukkonen, Tuula Palotie

“…TMJ arthritis can cause significant disturbances in TMJ function and growth without treatment. Our aim was to evaluate the effectiveness of medical treatments used to manage TMJ arthritis and how to evaluate the outcome of the treatment. …”
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Evaluation method and application for in-situ stress in No. 8+9 coal seam, southern Shenfu block, northeastern margin of Ordos Basin by Jiawei WU, Wei TANG, Yanhe ZHU, Cunwu WANG, Yongjing TIAN, Jingyu ZI, Jianghao YANG, Xian SHI

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Predictive factors for outcomes of sialoendoscopy by Hannah Damasceno Barreto, Jose Higino Steck, Samuel Serpa Steck, Diogo Silva de Carvalho, Carlos Takahiro Chone

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Interactive online learning method for students based on artificial intelligence by Cizhang Li, Wenfen Yin

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A Model Based on Neural Network to Predict Surface Settlement During Subway Station Construction: A Case Study of the Dongba-Zhongjie Station in Beijing, China by Jiaqi Zhang, Hua Jiang, Jinsen Wang, Jili Feng

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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Conclusions The combination of BRI and machine learning provides a non-invasive and effective method for predicting MetS and offers a promising strategy for its early prevention. …”
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A Review Of Road‒Related Soil Erosion: An Assessment Of Causes, Evaluation Techniques And Available Control Measures by Khoboso Elizabeth Seutloali, Heinrich Reinhard Beckedahl

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Hybrid modeling approaches for predicting COVID-19 mortality: A comparative study across USA, France, and India by B. Uppalaiah, D. Mallikarjuna Reddy, K. Rajalakshmi, P. Vignesh, V. Govindan, Siriluk Donganont

“…The models combine the adaptability of Gaussian Processes with the deep learning functionalities of RBM, LSTM, and CNN to improve prediction precision and uncertainty assessment. We utilize various evaluation metrics to determine the optimal hybrid model: Symmetric Mean Absolute Percentage Error (sMAPE) for accuracy, Continuous Ranked Probability Score (CRPS) for probabilistic forecasts, and Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for model selection. …”
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A multi-index evaluation system for tuff-asphalt mixtures exposed to long-term water damage based on the fractional grey prediction model. by Yanxia Cai, Jiaming Zhao, Chenchen Li, Jiachen Shi, Baoxin Zhang

“…A fractional grey prediction model (FGM) was employed to predict long-term behavior, while a comprehensive evaluation framework was developed using weighted averaging and relative scoring methods. …”
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INFLUENCE OF SIZE EFFECT ON EVALUATION OF TENSILE PROPERTIES USING SMALL PUNCH TEST (MT) by WANG WuLin, XU Tong, ZHONG JiRu, GUAN KaiShu, LIU Gang

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