Considering the effect of non-landslide sample selection on landslide susceptibility assessment by Youchen Zhu, Deliang Sun, Haijia Wen, Qiang Zhang, Qin Ji, Changming Li, Pinggen Zhou, Jianjun Zhao

“…In this study, we utilized Extreme Gradient Boosting and Random Forest algorithms, and four methods (Whole-area random selection method, Buffer method, Frequency Ratio method, and Analysis Hierarchy Process) were employed to select non-landslide samples for constructing the landslide susceptibility assessment model. …”
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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…Feature selection and optimization of input scenarios were achieved using a combination of particle swarm optimization (PSO) and manual methods. …”
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Providing a Robust Dynamic Pricing Model and Comparing It with Static Pricing in Multi-level Supply Chains Using a Game Theory Approach by Sara Mehrjoo, Hanan Amoozad Mahdirji, Jalil Heidary Dahoei, Seyyed Hossein Razavi Haji Agha, Mahnaz Hosseinzadeh

“…For data analysis, a genetic algorithm, particle accumulation optimization, and MATLAB software were employed. …”
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YOLOv8-Based Estimation of Estrus in Sows Through Reproductive Organ Swelling Analysis Using a Single Camera by Iyad Almadani, Mohammed Abuhussein, Aaron L. Robinson

“…Accurate and efficient estrus detection in sows is crucial in modern agricultural practices to ensure optimal reproductive health and successful breeding outcomes. …”
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Machine learning based assessment of hoarseness severity: a multi-sensor approach centered on high-speed videoendoscopy by Tobias Schraut, Anne Schützenberger, Tomás Arias-Vergara, Melda Kunduk, Matthias Echternach, Stephan Dürr, Julia Werz, Michael Döllinger

“…A videoendoscopic model was developed by selecting a suitable classification algorithm and a minimal-optimal subset of glottal parameters. …”
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A Cone-Beam Computed Tomography-Based Assessment of Safe Zones for Orthodontic Mini-Implant Placement in the Lateral Maxilla: A Retrospective Morphometric Study by Iva Jakovljevic, Pavle Milanovic, Milica Vasiljevic, Jovana Milanovic, Momir Z. Stevanovic, Nemanja Jovicic, Milos Stepovic, Vladimir Ristic, Dragica Selakovic, Gvozden Rosic, Aleksandra Arnaut

“…Also, the CBCT analysis algorithm may serve as a valuable tool for clinicians in determining optimal TAD placement in different dental regions.…”
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Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social... by A. A. Poguda, H. Tape

“…Thus, our system proves effective in providing valuable insights and optimizing audience interaction strategies. Conclusion. …”
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Temporal trends in the incidence of adverse effects of medical treatment in BRICS countries from 1990 to 2021: an age-period cohort analysis by Xingmin Wei, Xingmin Wei, Lu Jiang, Zhidong Zhang, Longjian Shang, Kun Liu, Xiaoang Qin, Gaoheng Ding, Lu Liu, Jianjun Wu

“…To strengthen AEMT prevention, these countries should prioritize optimizing existing healthcare resources, such as workforce training and surveillance systems. …”
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Automated Video Assistant Referee in Lead Climbing by Eliane Künzler, David Roder, Urs Stöcker, Peter Wolf

“…Next, we will compare our scoring algorithm representing given regulations with scores awarded. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…Abstract Background Metastatic spinal disease often leads to significant morbidity, and accurate prediction of postoperative outcomes can help optimize patient management and resource allocation. …”
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Cross-sectional imaging of speed-of-sound distribution using photoacoustic reversal beacons by Yang Wang, Danni Wang, Liting Zhong, Yi Zhou, Qing Wang, Wufan Chen, Li Qi

“…By picking up the PRB signal using a graph-based dynamic programing algorithm, we formulate a linear inverse model for pixel-wise SOS reconstruction and solve it with iterative optimization technique. …”
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Early Forest Fire Detection With UAV Image Fusion: A Novel Deep Learning Method Using Visible and Infrared Sensors by Kunlong Niu, Chongyang Wang, Jianhui Xu, Jianrong Liang, Xia Zhou, Kaixiang Wen, Minjian Lu, Chuanxun Yang

“…The results show that the improved registration method effectively aligns visible and infrared images, optimizing the fusion process and enhancing the use of multisource information. …”
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Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients by Yunjie Zhang, Songjian Tong, Junhui Yang, Jiawei Lin, Yifan Kong, Deyu Lu, Yan Chen, Yingchao Li, Linfeng Xu, Xiuyan Kong, Guoqing Zhu, Hao Zhang, Pixu Liu, Zhijie Yu, Jinglin Xia

“…Through recursive feature elimination (RFE), we systematically developed prediction models employing ten distinct ML algorithms. The SHAP algorithm was implemented to enhance model interpretability, while patient stratification was subsequently performed using PCA and K-means clustering to facilitate comprehensive prognostic analysis. …”
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Investigation of statistical methods used in prognostic prediction models for obstetric care: A 10 year‐span cross‐sectional study by Jing Tan, Chunrong Liu, Min Yang, Yiquan Xiong, Shiyao Huang, Yana Qi, Meng Chen, Lehana Thabane, Xinghui Liu, Lin He, Xin Sun

“…Conclusions The use of statistical methods is not yet optimal. Ten recommendations were offered to assist the statistical methods of prognostic prediction models in obstetric care.…”
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HPV-negative oropharyngeal carcinoma as a separate prognostkally unfavorable form of cancer, requiring new approaches to treatment (case report) by A. R. Gevorkov, A. V. Boyko, A. P. Polyakov, L. V. Bolotina, N. N. Volchenko, I. V. Rebrikova, A. М. Lemeshko, S. V. Shashkov

“…HPV-negative oropharyngeal cancer requires an optimized treatment algorithm and, possibly, more aggressive therapeutic measures, such as increased radiation doses. …”
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Integration of YOLOv9 Segmentation and Monocular Depth Estimation in Thermal Imaging for Prediction of Estrus in Sows Based on Pixel Intensity Analysis by Iyad Almadani, Aaron L. Robinson, Mohammed Abuhussein

“…Many researchers focus on improving reproductive health in sows and ensuring successful breeding by accurately identifying the optimal time of ovulation through estrus detection. …”
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The joint role of the immune microenvironment and N7-methylguanosine for prognosis prediction and targeted therapy in acute myeloid leukemia by Zhixiang Chen, Zhixiang Chen, Zhimei Chen, Xiaobo Huang, Xiaobo Huang, Xiaobo Huang, Xiongbin Yan, Xiongbin Yan, Xiaolin Lai, Xiaolin Lai, Shaoyuan Wang, Shaoyuan Wang

“…In vitro CCK-8 assays validated dactolisib’s monotherapy efficacy and synergistic cytotoxicity when combined with doxorubicin in AML cells.ConclusionThe IMEm7G gene signature established in our study effectively optimized the risk classification and predicted immunotherapy response in AML. …”
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Evaluation of MODIS and VIIRS BRDF Parameter Differences and Their Impacts on the Derived Indices by Chenxia Wang, Ziti Jiao, Yaowei Feng, Jing Guo, Zhilong Li, Ge Gao, Zheyou Tan, Fangwen Yang, Sizhe Chen, Xin Dong

“…This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. …”
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Assessment of prostate cancer aggressiveness through the combined analysis of prostate MRI and 2.5D deep learning models by Yalei Wang, Yuqing Xin, Baoqi Zhang, Fuqiang Pan, Xu Li, Manman Zhang, Yushan Yuan, Lei Zhang, Peiqi Ma, Bo Guan, Yang Zhang

“…Further, a clinical feature model (Clinic-LightGBM) was constructed using LightGBM to include clinical information. The optimal feature model was then combined with Clinic-LightGBM to establish a nomogram. …”
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Enhancing deep learning methods for brain metastasis detection through cross-technique annotations on SPACE MRI by Tassilo Wald, Benjamin Hamm, Julius C. Holzschuh, Rami El Shafie, Andreas Kudak, Balint Kovacs, Irada Pflüger, Bastian von Nettelbladt, Constantin Ulrich, Michael Anton Baumgartner, Philipp Vollmuth, Jürgen Debus, Klaus H. Maier-Hein, Thomas Welzel

“…Abstract Background Gadolinium-enhanced “sampling perfection with application-optimized contrasts using different flip angle evolution” (SPACE) sequence allows better visualization of brain metastases (BMs) compared to “magnetization-prepared rapid acquisition gradient echo” (MPRAGE). …”
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