Machine learning and SHAP value interpretation for predicting cardiovascular disease risk in patients with diabetes using dietary antioxidants by Xinyu Zhang, Sen Lin, Qingling Zeng, Lisheng Peng, Chaoguang Yan

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Prediction of Turfgrass Quality Using Multispectral UAV Imagery and Ordinal Forests: Validation Using a Fuzzy Approach by Alexander Hernandez, Shaun Bushman, Paul Johnson, Matthew D. Robbins, Kaden Patten

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Time series (ARIMA) as a tool to predict the temperature-humidity index in the dairy region of the northern desert of Mexico by José Luis Herrera-González, Rafael Rodríguez-Venegas, Martín Alfredo Legarreta-González, Pedro Antonio Robles-Trillo, Ángeles De-Santiago-Miramontes, Darithsa Loya-González, Rafael Rodríguez-Martínez

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Construction of a novel lipid drop-mitochondria-associated genetic profile for predicting the survival and prognosis of lung adenocarcinoma by Ruijuan Cai, Hongsheng Lin, Qianwen Cheng, Qiyuan Mao, Chuchu Zhang, Ying Tan

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Noise Pollution Prediction in a Densely Populated City Using a Spatio-Temporal Deep Learning Approach by Marc Semper, Manuel Curado, Jose Luis Oliver, Jose F. Vicent

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Predicting PbS Colloidal Quantum Dot Solar Cell Parameters Using Neural Networks Trained on Experimental Data by Hoon Jeong Lee, Arlene Chiu, Yida Lin, Sreyas Chintapalli, Serene Kamal, Eric Ji, Susanna M. Thon

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Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning by Yongguang Liang, Jingru Yang, Shuoyang Wei, Yanfei Liu, Shumeng He, Kang Zhang, Jie Qiu, Bo Yang

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Application of improved P-BEM in time varying channel prediction in 5G high-speed mobile communication system by Hui Yuechao

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Study on Noise Attenuation Characteristics of Hydrofoil with Specific Cavitation Number by He XIAOHUI, Liu ZHONGLE, Yang CHAO, Yuan ZHIYONG

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Enhancing gas concentration prediction and ventilation efficiency in deep coal mines: a hybrid DL-Koopman and Fuzzy-PID framework by Keyi Yuan, Ke Gao, Yujiao Liu

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Predicting Win-Loss outcomes in MLB regular season games – A comparative study using data mining methods by Soto Valero C.

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Epidemiological trends of hepatitis C incidence and death in Mainland China between 2004 and 2018 and its predictions to 2030 by Guo Tian, Yang Zheng, Yinghua He, Can Chen, Xiaobao Zhang, Yuxia Du, Shigui Yang, Tianan Jiang, Lanjuan Li

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Graph neural networks-based prediction of drug gene association of P2X receptors in periodontal pain by Pradeep Kumar Yadalam, Prabhu Manickam Natarajan, Seyed Ali Mosaddad, Artak Heboyan

“…Despite achieving a 65 percent accuracy rate, the GNN model demonstrated suboptimal predictive power for gene-drug interactions associated with oral pain. …”
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Predicting Pre- and Post-Diagnostic Depression in Women with Abnormal Pap Screening Tests: A Neural Network Approach by Irena Ilic, Goran Babic, Sandra Sipetic Grujicic, Ivana Zivanovic Macuzic, Milena Ilic, Ana Ravic-Nikolic, Vesna Milicic

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Indonesian Prostate Cancer Risk Calculator (IPCRC): An application for Predicting Prostate Cancer Risk (a Multicenter Study) by Prahara Yuri, Grace Wangge, Fatan Abshari, Adistra I.T.W.H Satjakoesoemah, Perdana R Perdana, Candra D.K Wijaya

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To Predict the Prognosis and Immunological Characteristics of Pancreatic Cancer Based on Disulfide-Death Gene Death-Related lncRNA by Zhihong Liao, Tianxing Dai, Feng Yuan, Kai Li, Guoying Wang

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Prediction of coating degradation based on “Environmental Factors–Physical Property–Corrosion Failure” two-stage machine learning by Weiting Chen, Lingwei Ma, Yiran Li, Dequan Wu, Kun Zhou, Jinke Wang, Zhibin Chen, Xin Guo, Zongbao Li, Thee Chowwanonthapunya, Xiaogang Li, Dawei Zhang

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Indonesian Prostate Cancer Risk Calculator (IPCRC): An application for Predicting Prostate Cancer Risk (a Multicenter Study) by Prahara Yuri, Grace Wangge, Fatan Abshari, Adistra I.T.W.H Satjakoesoemah, Perdana R Perdana, Candra D.K Wijaya

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Network Resource Allocation Method Based on Awareness–Prediction Joint Compensation for Low-Earth-Orbit Satellite Networks by Hang Di, Tao Dong, Zhihui Liu, Shuotong Wei, Qiwei Zhang, Dingyun Zhang

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NanoBinder: a machine learning assisted nanobody binding prediction tool using Rosetta energy scores by Palistha Shrestha, Chandana S. Talwar, Jeevan Kandel, Kwang-Hyun Park, Kil To Chong, Eui-Jeon Woo, Hilal Tayara

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