Critical review of patient outcome study in head and neck cancer radiotherapy by Jingyuan Chen, Yunze Yang, Chenbin Liu, Hongying Feng, Jason M. Holmes, Lian Zhang, Steven J. Frank, Charles B. Simone, II, Daniel J. Ma, Samir H. Patel, Wei Liu

“…This review critically evaluates the evolution of data-driven approaches in predicting patient outcomes in head and neck cancer patients treated with radiation therapy. …”
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Development, optimization and modelling of performance parameters for remote-controlled mechatronic precision planter using RSM and Hybrid PSO-ANN model by Vimalsinh Vala, Rajvir Yadav, Bikram Jyoti, Ali Salem, Ajay K Roul, Rahul Potdar, Ankur Srivastava, Ahmed Elbeltagi

“…The integration of PSO with prediction models offered insights into enhancing precision planting efficiency and overall crop yield in mechatronic precision planters.…”
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Label efficient phenotyping for Long COVID using electronic health records by Chuan Hong, Jun Wen, Harrison G. Zhang, Vidul Ayakulangara Panickan, Doris Y. Yang, Alicia W. Chen, Xin Xiong, Xuan Wang, Michele Morris, Sara Morini, Rahul Sangar, Andrew Dey, Malarkodi J. Samayamuthu, Katherine Liao, Clara-Lea Bonzel, Vidisha Tanukonda, Monika Maripuri, Jacqueline Honerlaw, Yuk-Lam Ho, Shyam Visweswaran, Isaac S. Kohane, Kelly Cho, Gabriel Brat, Zongqi Xia, Tianxi Cai

“…Developing efficient phenotyping algorithms is crucial to enabling risk prediction and effective management of Long COVID. …”
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Sodium Propionate Alleviates Atopic Dermatitis by Inhibiting Ferroptosis via Activation of LTBP2/FABP4 Signaling Pathway by Xie A, Li W, Ye D, Yin Y, Wang R, Wang M, Yu R

“…Analysis using three algorithms identified potential therapeutic targets of SP. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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How spatial resolution mediates canopy spectral diversity as a proxy for marsh plant diversity by Yi Fu, Yunlong Yao, Lei Wang, Huaihu Yi, Yuanqi Shan

“…The optimal spatial resolution for predicting plant diversity varies among different VIs, but VIs calculated from the same spectral bands consistently show similar predictive trends. …”
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Estimation of Canopy Chlorophyll Content of Apple Trees Based on UAV Multispectral Remote Sensing Images by Juxia Wang, Yu Zhang, Fei Han, Zhenpeng Shi, Fu Zhao, Fengzi Zhang, Weizheng Pan, Zhiyong Zhang, Qingliang Cui

“…The RF model, which outperforms the other models in terms of the prediction effect in multiple growth stages, can effectively predict the SPAD value in the leaves of apple trees and provide a reference for the growth status monitoring and precise management of orchards.…”
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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

“…These fields are essential for both mapping ice distribution and predicting icing using physical models combined with numerical weather prediction systems. …”
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Tensor RT optimized driver drowsiness detection system using edge device by Chandramohan Dhasarathan, Sambasivam Gnanasekaran, Arnab Pattanayak, Gourav Kumar, Kartik Vig, Vaibhav Narain, K.M. Deva Narayan, Sunidhi Garg

“…The system uses transfer learning techniques for implementing CNN model algorithms to analyze live video from the camera module, allowing for real-time detection of driver behavior such as fatigue or distraction. …”
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Identifying Therapeutic Targets and Potential Drugs for Diabetic Retinopathy: Focus on Oxidative Stress and Immune Infiltration by Peng H, Hu Q, Zhang X, Huang J, Luo S, Zhang Y, Jiang B, Sun D

“…Immune infiltration analysis and regulatory networks were constructed. Drug prediction was validated through molecular docking, and hub gene expression was confirmed in dataset and animal models.Results: Compared to the control group, 91 DEOSGs were found. …”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

“…Then, an efficient deep learning method was proposed based on this dataset to enhance the predictive performance.ResultsThe prediction accuracy achieved for the yellowing degree, browning degree, and drying degree were 83.0%, 90.5%, and 75.6% respectively. …”
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Constructing a Glioblastoma Prognostic Model Related to Fatty Acid Metabolism Using Machine Learning and Identifying F13A1 as a Potential Target by Yushu Liu, Hui Deng, Ping Song, Mengxian Zhang

“…On the basis of 10 kinds of machine learning methods, we used 101 combinations of algorithms to construct prognostic models and obtain the best model. …”
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Transfer Learning Estimation and Transferability of LNC and LMA Across Different Datasets by Yingbo Wang, Mengzhu He, Lin Sun, Yong He, Zengwei Zheng

“…The LNC and LMA estimation performance in transfer models established by partial least squares regression (PLS), support vector regression (SVR), extreme gradient boosting (XGB), and random forest regression (RFR) algorithms across different datasets were employed, in which the RFR transfer models performed good prediction results. …”
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Identification of fermented soy sauce and blended soy sauce based on dielectric spectra by Yingman Xie, Jiayao Zhao, Chao Mao, Huiyun Pang, Pengfei Ye, Xiangwei Chen, Hongfei Fu, Yequn Wang, Yunyang Wang

“…The effects of selecting characteristic variables on model prediction using the full spectra (FS), principal component analysis (PCA), and successive projection algorithm (SPA) were compared. …”
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AI illuminates paths in oral cancer by Devesh U. Kapoor, Pushpendra Kumar Saini, Narendra Sharma, Ankul Singh, Bhupendra G. Prajapati, Gehan M. Elossaily, Summya Rashid

“…The role of artificial intelligence in prognosis of oral cancer including predictive modeling, identification of prognostic factors and risk stratification also discussed significantly in this review. …”
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Machine Learning Classification of First-Onset Drug-Naive MDD Using Structural MRI by Donghwa Kim, Pilsung Kang, Junhong Kim, Czang Yeob Kim, Jong-Ha Lee, Sangil Suh, Moon-Soo Lee

“…We aimed to determine whether it is possible to reliably train a highly accurate predictive classification algorithm, even with the first onset of drug-naive adolescent MDD, solely using structural magnetic resonance imaging and without using any other clinical data from the patients. …”
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The interaction between temperature and precipitation on the potential distribution range of Betula ermanii in the alpine treeline ecotone on the Changbai Mountain by Yu Cong, Yongfeng Gu, Wen J. Wang, Lei Wang, Zhenshan Xue, Yingyi Chen, Yinghua Jin, Jiawei Xu, Mai-He Li, Hong S. He, Ming Jiang

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Artificial intelligence technology in ophthalmology public health: current applications and future directions by ShuYuan Chen, Wen Bai, Wen Bai

“…AI offers significant improvements in ophthalmic data management, disease screening and monitoring, risk prediction and early warning systems, medical resource allocation, and health education and patient management. …”
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Assessment of the impact of a new sequential approach to antimicrobial use in young febrile children in the emergency department (DIAFEVERCHILD): a French prospective multicentric... by Elsa Tavernier, Elise Launay, Christèle Gras Le Guen, Gaelle Hubert, Cécile Feildel Fournial, Anne Chauvire-Drouard, Fleur Lorton

“…The aims of this study are to demonstrate that using a procalcitonin (PCT) rapid test-based prediction rule (1) would not be inferior to usual practice in terms of morbidity and mortality (non-inferiority objective) and (2) would result in a significant reduction in antibiotic use (superiority objective).Methods and analysis This prospective multicentric cluster-randomised study aims to include 7245 febrile children aged 6 days to 3 years with a diagnosis of fever without source in 26 participating EDs in France and Switzerland during a 24-month period. …”
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Design Automation of Sheet Materials Cutting Maps in a Production by A. I. Yakimov, D. A. Denisevich, E. A. Yakimov

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