Trajectory of breastfeeding among Chinese women and risk prediction models based on machine learning: a cohort study by Yi Liu, Jie Xiang, Ping Yan, Yuanqiong Liu, Peng Chen, Yujia Song, Jianhua Ren

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Predictive modelling and ranking: Azadirachta indica compounds through indices and multi-criteria decision-making techniques by D. S. Anuradha, B. Jaganathan

“…Regression analysis and multi-criteria decision-making methods were employed for predictive modeling and compound ranking.ResultsStatistical metrics demonstrated the predictive power of the models. …”
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Predictive modeling for the adsorptive and photocatalytic removal of phenolic contaminants from water using artificial neural networks by Shahzar Hafeez, Ayesha Ishaq, Azeem Intisar, Tariq Mahmood, Muhammad Imran Din, Ejaz Ahmed, Muhammad Rizwan Tariq, Muhammad Amin Abid

“…To overcome these limitations, the modeling and optimization of water treatment methods is required. …”
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Dual statistical models link baseline visual attention measure to risk for significant symptomatic concussion in sports by Lisa A Spielman, Jun Maruta, Jamshid Ghajar

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Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus by Lu-Xi Zou, Xue Wang, Zhi-Li Hou, Ling Sun, Jiang-Tao Lu

“…The risk variables for DKD development were ranked and selected to establish forecasting models. The performance of models was further evaluated by the indexes of sensitivity, specificity, positive predictive value, negative predictive value, accuracy, as well as F1 score, using the testing dataset. …”
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Application of Mechanistic Models and the Gaussian Process Model to Predict Bacterial Growth on Baby Spinach During Refrigerated Storage by Sriya Sunil, Sarah I. Murphy, Ruixi Chen, Wei Chen, Joseph Guinness, Li-Qun Zhang, Renata Ivanek, Martin Wiedmann

“…Models that predict bacterial growth in food products can help industry with decision-making with regard to microbial food spoilage. …”
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A dynamic prediction method for surface mining subsidence based on dynamic probability integral model and Logistic model by Lei HAN, Xinxin QI, Tianjun WANG, Chunmin PEI, Xudong WANG

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Performance Comparison between the Specific and Baseline Prediction Models of Ecotoxicity for Pharmaceuticals: Is a Specific QSAR Model Inevitable? by Qingwei Bu, Qingshan Li, Yun Liu, Chun Cai

“…Nonetheless, it should be noted that 95% prediction intervals spread over approximately four orders of magnitude for both tested QSAR models specifically for pharmaceuticals.…”
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Development of a Comprehensive Model for Predicting Stock Prices in the Stock Market Using an Interpretive Structural Modeling Approach by Shiva Rezaeyan, Mohammad Taleghani, Azita Sherejsharifi

“…ObjectiveThis study aims to create a comprehensive stock price prediction model for the Tehran Stock Exchange by employing both fuzzy Delphi and interpretive structural modeling techniques. …”
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Predicting precipitation and NDVI utilization of the multi-level linear mixed-effects model and the CA-markov simulation model by Fatima Belhaj, Hlila Rachid, Ouallali Abdessalam, Aqil Tariq, Belkendil Abdeldjalil, Beroho Mohamed, Hassan Alzahrani, Hajra Mustafa, Hesham Mohamed El-Askary

“…The CA-Markov model was employed to predict the vegetation indices for 2029 and 2040 using 1999, 2009, and 2019 data. …”
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VVC coded distortion prediction model based on frame-level transform coefficient modeling of generalized Gaussian distribution by Yiyin GU, Hongkui WANG, Haibin YIN

“…In versatile video coding (VVC), a variety of advanced coding tools work together to achieve excellent coding performance.Compared with high efficient video coding (HEVC), the transform coefficient distribution (TCD) of VVC has sharper peaks.In order to solve this phenomenon, the probability density function (PDF) of frame-level TCD was modeled, and a frame-level coding distortion prediction model based on statistical modeling was proposed, which modeled frame-level distortion as a function of TCD distribution parameters and quantization parameters.The experimental results show that compared with the Laplace distribution and Cauchy distribution, the generalized Gaussian distribution has the best performance in TCD probability density fitting.The prediction results based on the generalized Gaussian distribution distortion prediction model are closest to the actual coding distortion.…”
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Comparison of ARIMA model and XGBoost model for prediction of human brucellosis in mainland China: a time-series study by Wei Wu, Peng Guan, Mirxat Alim, Guo-Hua Ye, De-Sheng Huang, Bao-Sen Zhou

“…The XGBoost model is more suitable for prediction cases of human brucellosis in mainland China.…”
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D3: A Small Language Model for Drug-Drug Interaction prediction and comparison with Large Language Models by Ahmed Ibrahim, Abdullah Hosseini, Salma Ibrahim, Aamenah Sattar, Ahmed Serag

“…Expert evaluations further confirmed that D3’s predictions were clinically relevant and closely aligned with those of larger models. …”
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Research on time series prediction model for multi-factor environmental parameters in facilities based on LSTM-AT-DP model by Longwei Liang, Longwei Liang, Hui Shi, Hui Shi, Zhaoyuan Wang, Shengjie Wang, Changhong Li, Ming Diao

“…IntroductionExisting facility environment prediction models often suffer from low accuracy, poor timeliness, and error accumulation in long-term predictions under multifactor nonlinear coupling conditions. …”
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Evaluating crop yield prediction models in illinois using aquacrop, semi-physical model and artificial neural networks by Vishal Gautam, Abdul Gani, Shray Pathak, Anoop Kumar Shukla

“…For both corn and soybean yields, the ANN model showed the highest prediction accuracy among the other models. …”
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Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach by Rui Xue, Daniel (Jian) Sun, Shukai Chen

“…This paper proposes an interactive multiple model (IMM) filter algorithm-based model to predict short-term passenger demand. …”
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Machine learning models and dimensionality reduction for improving the Android malware detection by Pablo Morán, Antonio Robles-Gómez, Andres Duque, Llanos Tobarra, Rafael Pastor-Vargas

“…This work first proposes a new efficient dimensionality reduction of features, as well as the application of several supervised machine learning algorithms for prediction purposes. Predictive models based on Random Forest are found to achieve the most promising results. …”
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A photoconversion model for full spectral programming and multiplexing of optogenetic systems by Evan J Olson, Constantine N Tzouanas, Jeffrey J Tabor

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Non-Destructive Detection of Current Internal Disorders and Prediction of Future Appearance in Mango Fruit Using Portable Vis-NIR Spectroscopy by Jasciane da Silva Alves, Bruna Parente de Carvalho Pires, Luana Ferreira dos Santos, Tiffany da Silva Ribeiro, Kerry Brian Walsh, Ederson Akio Kido, Sergio Tonetto de Freitas

“…A recommendation is made for the consideration of ensemble models in future. The ability to predict the development of the disorder using spectra of at-harvest fruit offers the potential to guide postharvest practices and reduce incidence of internal disorders in mangoes.…”
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Prediction of absolute bioavailability of medicines in children: based on predicted pediatric clearance from adults by Iftekhar Mahmood

“…Systemic and oral clearances of these medicines in children were predicted using age-dependent exponent (ADE) allometric model using observed adult clearance values. …”
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