A Multi-Omics Prognostic Model Capturing Tumor Stemness and the Immune Microenvironment in Clear Cell Renal Cell Carcinoma by Beibei Xiong, Wenqiang Liu, Ying Liu, Tong Chen, Anqi Lin, Jiaao Song, Le Qu, Peng Luo, Aimin Jiang, Linhui Wang

“…Recognizing tumor stemness helps to predict treatment efficacy, recurrence, and drug resistance, informing treatment strategies and enhancing ccRCC patient outcomes.…”
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Screening Model for Bladder Cancer Early Detection With Serum miRNAs Based on Machine Learning: A Mixed‐Cohort Study Based on 16,189 Participants by Cong Lai, Zhensheng Hu, Jintao Hu, Zhuohang Li, Lin Li, Mimi Liu, Zhikai Wu, Yi Zhou, Cheng Liu, Kewei Xu

“…Five machine learning algorithms were utilized to develop screening models for BCa using the training dataset. …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…We compare various KD algorithms to identify the technique that produces a smaller model with the modest accuracy drop. …”
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SIGMAR1 screened by a GPCR-related classifier regulates endoplasmic reticulum stress in bladder cancer by Jingming Zhuang, Yang Wang, Xinyong Wu, Zijing Peng, Zhengnan Huang, Chao Zhao, Bing Shen

“…Thereafter, multiple algorithms were employed for the screening of GPCRs and immune cells related to the prognosis of BC. …”
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A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce regionZENODO by Rodrigo de Q. Miranda, Rodolfo L.B. Nóbrega, Anne Verhoef, Estevão L.R. da Silva, Jadson F. da Silva, José C. de Araújo Filho, Magna S.B. de Moura, Alexandre H.C. Barros, Alzira G.S.S. Souza, Wanhong Yang, Hui Shao, Raghavan Srinivasan, Feras Ziadat, Suzana M.G.L. Montenegro, Maria do S.B. Araújo, Josiclêda D. Galvíncio

“…We developed a machine learning framework that integrates the Soil-Landscape Estimation and Evaluation Program (SLEEP) with gradient boosting to predict soil properties at regional scales and multiple depths. …”
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Development and validation of a nomogram for differentiating immune checkpoint inhibitor-related pneumonitis from pneumonia in patients undergoing immunochemotherapy: a multicenter... by Linli Duan, Guanglu Liu, Zijie Huang, Rong Chen, Di Mo, Yuxiao Xia, Jiazhu Hu, Mengzhang He

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Dedicated homeless clinics reduce inappropriate emergency department utilization by Chad T. Holmes, Katherine A. Holmes, Andrew MacDonald, Frank R. Lonergan, Joel J. Hunt, Sajid Shaikh, Radhika Cheeti, James P. D'Etienne, Nestor R. Zenarosa, Hao Wang

“…The New York University algorithm was used to determine appropriate ED utilization. …”
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An Upscaling-Based Strategy to Improve the Ephemeral Gully Mapping Accuracy by Solmaz Fathololoumi, Daniel D. Saurette, Harnoordeep Singh Mann, Naoya Kadota, Hiteshkumar B. Vasava, Mojtaba Naeimi, Prasad Daggupati, Asim Biswas

“…Employing the Random Forest (RF) algorithm, this study executed three distinct strategies for EGs identification. …”
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Deep and Domain Specific Feature-Based Cervical Cancer Classification Using Support Vector Machine Optimized With Particle Swarm Optimization by Ritesh Maurya, Lucky Rajput, Satyajit Mahapatra

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New Methodologies for the Optimization of Operational Parameters of Bio Gas Power Plants: A Review by Sidahmed Sidi Habib, Shuichi Torri, Kavitha Mol S.

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Constructing a tumor immune microenvironment-driven prognostic model in acute myeloid leukemia using bioinformatics and validation data by Amir Abbas Navidinia, Ali Keshavarz, Bentol Hoda Kuhestani Dehaghi, Reza Khayami, Najibe Karami, Vahid Amiri, Mehdi Allahbakhshian Farsani

“…ROC analysis demonstrated predictive accuracy (AUC: 63.38–68.5% for 1–5-year survival). …”
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Bundled assessment to replace on-road test on driving function in stroke patients: a binary classification model via random forest by Lu Huang, Lu Huang, Xin Liu, Jiang Yi, Yu-Wei Jiao, Tian-Qi Zhang, Guang-Yao Zhu, Shu-Yue Yu, Zhong-Liang Liu, Min Gao, Xiao-Qin Duan

“…Furthermore, the established random forest classification model has demonstrated efficacy in predicting on-road test outcomes, which is worthy of further clinical application.…”
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Mapping recent timber harvest activity in a temperate forest using single date airborne LiDAR surveys and machine learning: lessons for conservation planning by G. Burch Fisher, Andrew J. Elmore, Matthew C. Fitzpatrick, Darin J. McNeil, Jeff W. Atkins, Jeffery L. Larkin

“…In this paper, we develop a timber harvest mapping workflow using machine learning (XGBoost algorithm) and single campaign airborne light detection and ranging (LiDAR) surveys for the state of Pennsylvania, USA. …”
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Integrative genomic analysis and diagnostic modeling of osteoporosis: unraveling the interplay of autophagy, osteogenesis, adipogenesis, and immune infiltration by Lin-Jing Han, Jian-Zong Zhu, Jian-Zong Zhu, Hong-Cai Liu, Xiao-Sheng Lin, Xiao-Sheng Lin, Shu-Zhong Yang

“…Our study formulates a predictive diagnostic model for OP by analyzing differential gene expression, thereby improving early diagnosis and therapeutic approaches.MethodsUsing GSE62402, GSE56815, and GSE35958 datasets from the Gene Expression Omnibus (GEO) database, we identified differentially expressed genes (DEGs) via R packages, and evaluated the underlying molecular mechanisms by network analysis. …”
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Machine learning assisted estimation of total solids content of drilling fluids by B.T. Gunel, Y.D. Pak, A.Ö. Herekeli, S. Gül, B. Kulga, E. Artun

“…In the final stage, different evaluation metrics were employed to evaluate and compare the performance of different classes of machine learning models. Among all algorithms tested, random forests algorithm was found to be the best predictive model resulting in consistently high accuracy. …”
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Permeability evolution of the thick Cretaceous aquifer and the high-level bed separation water accumulation model during coal mining by Wei QIAO, Xiangsheng MENG, Juan YANG, Liangang LI, Qijing LIANG, Mengnan LIU, Zhihe TAO, Changmin HAN, Weiteng KONG

“…Hydraulic tomography inversion technology, based on the Simultaneous Sequential Linear Estimation (SimSLE) algorithm, was used to analyze the permeability evolution of the aquifer during mining. …”
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Comprehensive analyses of telomerase component DKC1 and its association with clinical, molecular and immune landscapes in uterine corpus endometrial carcinoma by Chenxi Sun, Xu Liu, Tiantian Liu, Chenliu Fan, Yang Jiang, Binggen Li, Huiyang Yuan, Chengyun Zheng, Dawei Xu

“…Higher DKC1 expression predicted shorter patient overall and progression-free survival. …”
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Enrollment and Retention Outcomes from the Veterans Health Administration for a Remote Digital Health Study: Multisite Observational Study by Jaclyn A Pagliaro, Lauren K Wash, Ka Ly, Jenny Mathew, Alison Leibowitz, Ryan Cabrera, Jolie B Wormwood, Varsha G Vimalananda

“…Device and survey data were combined with VA clinical and utilization data to develop a predictive algorithm for clinical decompensation. The geographic distribution of enrolled patients was mapped by county. …”
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Impact of Temporal Resolution on Autocorrelative Features of Cerebral Physiology from Invasive and Non-Invasive Sensors in Acute Traumatic Neural Injury: Insights from the CAHR-TBI... by Nuray Vakitbilir, Rahul Raj, Donald E. G. Griesdale, Mypinder Sekhon, Francis Bernard, Clare Gallagher, Eric P. Thelin, Logan Froese, Kevin Y. Stein, Andreas H. Kramer, Marcel J. H. Aries, Frederick A. Zeiler

“…These high-resolution data streams come from various invasive/non-invasive sensor technologies and challenge clinicians, as they are difficult to integrate into management algorithms and prognostic models. Data reduction techniques, like moving average filters, simplify data but may fail to address statistical autocorrelation and could introduce new properties, affecting model utility and interpretation. …”
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D-Band 4.6 km 2 × 2 MIMO Photonic-Assisted Terahertz Wireless Communication Utilizing Iterative Pruning Deep Neural Network-Based Nonlinear Equalization by Jingwen Lin, Sicong Xu, Qihang Wang, Jie Zhang, Jingtao Ge, Siqi Wang, Zhihang Ou, Yuan Ma, Wen Zhou, Jianjun Yu

“…Additionally, the pruning process contributed to a decrease in network complexity, with a maximum reduction of 85.9% for 10 GBaud signals and 63.0% for 30 GBaud signals. …”
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