A model predictive control method for directional borehole trajectories in underground coal mines by Hao LI, Ningping YAO, Chengda LU, Jinbao ZHANG, Hongchao WEI, Jiajun WU, Jinyu LI

“…Finally, the control algorithm was validated using the drilling data from a coal mine in Hancheng City, Shaanxi Province. …”
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Winter Wheat Yield Prediction and Influencing Factors Analysis Based on FourierGNN–Random Forest Combined Modeling by Jianqin Ma, Yijian Chen, Bifeng Cui, Yu Ding, Xiuping Hao, Yan Zhao, Junsheng Li, Xianrui Su

“…Matrix multiplication in Fourier space was performed to predict yield, while the Random Forest algorithm was employed to quantify the contribution of various yield factors to winter wheat yield. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…Deep learning models, while effective, are associated with high computational costs and large data requirements. …”
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Leveraging diverse cell-death patterns to predict to predict prognosis and immunotherapy in hepatocellular carcinoma by Xiaoxiang Zhang, Dongxiao Ding, Dianqian Wang, Yunsheng Qin

“…The immune infiltration status and immune function of the signature were analyzed by ESTIMATE algorithm and ssGSEA algorithm. TIDE score, IPS and immune checkpoints expression and IC50 value were utilized to predict chemosensitivity and immunotherapy response. …”
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Quantifying Spatiotemporal Changes in Supraglacial Debris Cover in Eastern Pamir from 1994 to 2024 Based on the Google Earth Engine by Hehe Liu, Zhen Zhang, Shiyin Liu, Fuming Xie, Jing Ding, Guolong Li, Haoran Su

“…Between 1994 and 2024, while the total glacier area decreased by −2.57 ± 0.70%, the debris-covered areas expanded upward at a rate of +1.64 ± 0.10% yr⁻¹. …”
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Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT. by Haoran Zhang, Jinlong Liu, Danyang Su, Zhen Bai, Yan Wu, Yuanbo Ma, Qiuju Miao, Mingyue Wang, Xiaopeng Yang

“…Among all models used for diagnosing fatty liver, the 2D radiomics model based on the random forest algorithm achieved the highest AUC (0.973), while the 2D radiomics model based on the Bagging decision tree algorithm showed the highest sensitivity (0.873), specificity (0.939), accuracy (0.864), precision (0.880), and F1 score (0.876).…”
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Multiple objectives escaping bird search optimization and its application in stock market prediction based on transformer model by Dedai Wei, Zimo Wang, Minyu Qiu, Juntao Yu, Jiaquan Yu, Yurun Jin, Xinye Sha, Kaichen Ouyang

“…To address this issue, this paper proposes an innovative multi-objective optimization algorithm—the Multi-Objective Escape Bird Algorithm (MOEBS)—and introduces the MOEBS-Transformer architecture to enhance the efficiency and effectiveness of hyper-parameter optimization for Transformer models. …”
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Machine Learning-Based Pathomics Model to Predict the Prognosis in Clear Cell Renal Cell Carcinoma by Xiangyun Li MD, MS, Xiaoqun Yang MD, PhD, Xianwei Yang BSc, Xin Xie MD, PhD, Wenbin Rui MD, PhD, Hongchao He MD, PhD

“…Immune-related genes, including CTLA4, CD80, and TIGIT, were highly expressed in Cluster 2, while the VHL and PBRM1 genes, along with mutations in the PI3K-Akt, HIF-1, and MAPK signaling pathways, exhibited mutation rates exceeding 40% in both subtypes. …”
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Long‐Term Trend and Seasonal Cycles of Gap‐Free Downscaled Diurnal/Nocturnal LST and the Interaction to Functional Plant Trait Under Tropical Monsoon Climate by Pham Viet Hoa, Nguyen An Binh, Giang Thi Phuong Thao, Nguyen Ngoc An, Pham The Trinh, Nguyen Quang Tuan, Nguyen Cao Hanh

“…Firstly, Moderate Resolution Imaging Spectroradiometer (MODIS) LST 1,000 m of both daytime and nighttime were downscaled to a finer resolution of 250 m using the Random Forest algorithm. The Whittaker algorithm was then applied to obtain gap‐free LST products due to the typical cloud cover under tropical monsoon climate. …”
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Development and feasibility testing of an AI-powered chatbot for early detection of caregiver burden: protocol for a mixed methods feasibility study by Ravi Shankar, Anjali Bundele, Amanda Yap, Amartya Mukhopadhyay

“…Primary outcomes include concordance between caregiver burden levels detected by the NLP algorithm and validated assessment scores at both timepoints. …”
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Evaluating Supervised Learning Classifier Performance for OFDM Communication in AWGN-Impacted Systems by Lavanya Vaishnavi D A, Anil Kumar C

“…With the obtained results we have proposed an hybrid model by implementing various ML algorithm for existing communication system pertaining to the receiver for reconstruction of the received signals by training the system using the data transmitted and received data is subjected to testing proposed ML algorithm. …”
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Diagnostic value of lung ultrasound B-lines for evaluating left ventricular filling pressure by Takahiro Sakamoto, Toshihiko Asanuma, Hiroyuki Sasaki, Hiroshi Kawahara, Kazuhiko Uchida, Akihiro Endo, Hiroyuki Yoshitomi, Kazuaki Tanabe

“…In patients who underwent lung ultrasound while they were hemodynamically stable and were followed up for prognosis (median, 730 days; n = 75), 14 hospitalisations for HF were observed. …”
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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…Subsequently, to effectively improve detection accuracy while reducing model parameters and computational load, we implemented several improvements to the deep learning algorithm, including the MGFF (Multi-Scale Grouped Feature Fusion) module, the LSKA-SPPF (Large Separable Kernel Attention-Spatial Pyramid Pooling-Fast) module, and the GNDCDH (Group Norm Detail Convolution Detection Head). …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). Bayesian optimization was used for global tuning of network structural parameters, while ASFSSA was applied to fine-tune the initial weights and thresholds, improving convergence efficiency and predictive accuracy. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Subsequently, the refined data undergoes feature selection employing an improved pigeon-inspired optimizer (PIO) algorithm. This operation eliminates redundant and irrelevant features, consequently reducing data dimensionality while maintaining critical information. …”
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Application of radiomics-based prediction model to predict preoperative lymph node metastasis in prostate cancer: a systematic review and meta-analysis by Yanghuang Zheng, Yuelin Du, Biao Zhang, Helin Zhang, Panfeng Shang, Zizhen Hou

“…The subgroup analysis showed that the least absolute shrinkage and selection operator regression algorithm had the higher diagnostic sensitivity, with a pooled sensitivity of 0.96 (95% CI [0.90 - 1.00]) (p = 0.02), while the random forest algorithm was the opposite, with a pooled sensitivity of 0.48 (95% CI [0.16 - 0.80]) (p = 0.01). …”
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MEL-YOLO: A Novel YOLO Network With Multi-Scale, Effective, and Lightweight Methods for Small Object Detection in Aerial Images by Yang Yang, Fangtao Feng, Guisuo Liu, Juxing Di

“…Secondly, the improved model incorporates a decoupled detection head, which separates the classification task from the localization task, thereby improving detection accuracy while increasing detection complexity. Furthermore, we explore the Soft-NMS algorithm to effectively mitigate small object occlusion and reduce missed detection. …”
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A review of approaches to assessment of potential radon hazard of land plots by A. S. Vasilyev, D. V. Kononenko, T. A. Kormanovskaya, K. A. Saprykin

“…According to Rosstat statistics, in recent years there has been a tendency in the Russian Federation to increase the intensity of construction, while both the number of buildings put into operation and their total area are increasing. …”
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Acceptability of Guided Symptom Entry and Asynchronous Clinical Communication Software Among Primary Care Staff: Qualitative Study by Riina Raudne, Taavi Tillmann

“…ObjectiveThis study aimed to investigate a patient-facing algorithm-guided symptom-entry software (developed by Certific OÜ, Estonia), which also supports subsequent asynchronous communication, for its acceptability and perceived utility to primary health care providers. …”
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Mediastinal staging lymph node probability map in non-small cell lung cancer by J. Bordas-Martinez, J.L. Vercher-Conejero, G. Rodriguez-González, P.C. Notta, C. Martin Cabeza, N. Cubero, R.M. Lopez-Lisbona, M. Diez-Ferrer, C. Tebé, S. Santos, M. Cortes-Romera, A. Rosell

“…Promising predictive algorithms for lymph nodes have been reported for each technique, both individually and in combination. …”
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