Cell Death and Senescence‐Based Molecular Classification and an Individualized Prediction Model for Lung Adenocarcinoma by Pan Wang, Chaoqi Zhang, Peng Wu, Zhihong Zhao, Nan Sun, Qi Xue, Shugeng Gao, Jie He

“…The clinical utility of CDSI was further validated using 9185 pan‐cancer samples, demonstrating the broad relevance of our prediction model across various cancer types and its potential clinical implications for cancer management.…”
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An interpretable deep learning model for the accurate prediction of mean fragmentation size in blasting operations by Baoqian Huan, Xianglong Li, Jianguo Wang, Tao Hu, Zihao Tao

“…On the test set, the model maintained high prediction accuracy, with an R 2 value of 0.9105 and an RMSE of 0.0403. …”
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The Hybrid Model: Prediction-Based Scheduling and Efficient Resource Management in a Serverless Environment by Louai Shiekhani, Hui Wang, Wen Shi, Jiahao Liu, Yuan Qiu, Chunhua Gu, Weichao Ding

“…To address these issues, we propose a multi-level scheduling solution: the Hybrid Model. This model is designed to reduce the frequency of cold starts while maximizing container utilization. …”
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Flow similarity model predicts allometric relationships among Acer platanoides L. branches by Charles A. Price, Gregory A. Dahle, Jason C. Grabosky

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Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers by Hengjun Wan, Huaju Tian, Cheng Wu, Yue Zhao, Daiying Zhang, Yujie Zheng, Yuan Li, Xiaoxia Duan

“…Herein, we constructed a multidimensional postoperative delirium risk‐prediction model incorporating multiple demographic parameters and blood biomarkers to enhance prediction accuracy. …”
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The Prediction of Serum C-Reactive Protein Concentration Using Nonlinear Mixed-Effects Model by Suk Joo Bae, Gyu Ri Kim, Sun Geu Chae, Yeesuk Kim

“…The bi-exponential model with random effects is applied to predict temporal CRP concentrations in patients after hip surgery. …”
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Multi-Step Parking Demand Prediction Model Based on Multi-Graph Convolutional Transformer by Yixiong Zhou, Xiaofei Ye, Xingchen Yan, Tao Wang, Jun Chen

“…The results show that the MGCN–Transformer model has a MAE, RMSE, and R² error index of 0.26, 0.42, and 95.93%, respectively, in the multi-step prediction task of parking demand, demonstrating its superior predictive accuracy compared to other benchmark models.…”
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A Prediction Model for External Root Resorption of the Second Molars Associated With Third Molars by Zhengwei Kou, Wuyang Zhang, Chen Li, Yu Zhang, Zijian Song, Yuzhen Zou, Haijing Wang, Zhenghua Liu, Bahetibieke Huerman, Tiange Deng, Kaijin Hu, Yang Xue, Ping Ji

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Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model. by Gahao Chen, Ziwei Yang

“…Current machine learning (ML) models demonstrate suboptimal predictive performance in KD treatment response prediction, primarily due to their limited ability to effectively process categorical variables and interpret tabular clinical data. …”
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A blood test-based machine learning model for predicting lung cancer risk by Lihi Schwartz, Naor Matania, Matanel Levi, Teddy Lazebnik, Teddy Lazebnik, Shiri Kushnir, Noga Yosef, Assaf Hoogi, Dekel Shlomi, Dekel Shlomi

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A Dual Convolution Model for Grating Lobe Prediction in Directivity of Parametric Array Loudspeakers by Shangming Mei, Yihua Hu, Mohammed Alkahtani, Mohammad Nasr Esfahani

“…The efficacy of the proposed model, compared with traditional convolutional approaches, has been validated through benchmark studies and experimental measurements demonstrating high accuracy in predicting grating lobes.…”
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Inflammation-nutrition biomarker model for survival prediction in lung cancer patients with concurrent tuberculosis by Hongqi Zhou, Zihao Zhao, Jinhai Wang, Weiyun Jin, Bensong Xian, Lindi Li, XiangWen Nie, WeiWei Wu, Ran Chen, QiZhen Xie, HaiXia Wu, WeiWei Jiang, Min Tang, YuXin Li

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Stacked ensemble model for accurate crop yield prediction using machine learning techniques by Ramesh V, Kumaresan P

“…Our work proposes a stacked ensemble model designed for the purpose of predicting crop yield. …”
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Dynamic flood risk prediction in Houston: a multi-model machine learning approach by Shuchi Mishra, Aproorv Bajpai, Agradeep Mohanta, Biplab Banerjee, Shrishti Rajput, Sudipta Kundu

“…This study highlights ANN's robustness in flood prediction, providing a crucial tool for urban planning and fostering resilient, sustainable development.…”
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Predicting Mortality in Elderly Patients with Hypertensive Crises: Development and Validation of a Risk Model by Erkan Boga

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Solar radiation prediction: A multi-model machine learning and deep learning approach by C Vanlalchhuanawmi, Subhasish Deb, Md. Minarul Islam, Taha Selim Ustun

“…A feature selection process using Pearson’s coefficient identified the most relevant inputs, while quantile regression was employed for uncertainty assessment, mean prediction interval, and prediction interval coverage probability models. …”
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Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank by Heli Julkunen, Juho Rousu

“…In a clinical cardiovascular risk prediction scenario using the established QRISK3 model, the method adds predictive value by identifying interactions beyond the age interaction effects currently included. …”
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Prediction Model of 30-Days Postoperative Pneumonia in Elderly Patient Undergoing Abdominal Surgery by Noto Dwimartutie, Harini Oktadiana, Gurmeet Singh, Wifanto Saditya Jeo, Kuntjoro Harimurti

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Simulate Congestion Prediction in a Wireless Network Using the LSTM Deep Learning Model by Nada Badr Jarah

“…A wireless connection was made using the Android system, and congestion was predicted based on the analysis of wireless communication packages around the access point using the LSTM deep learning model. …”
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Machine learning-based prediction of diabetic peripheral neuropathy: model development and clinical validation by Meng Sun, Xingling Sun, Fei Wang, Li Liu

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