Examining the Impact of Topography and Vegetation on Existing Forest Canopy Height Products from ICESat-2 ATLAS/GEDI Data by Yisa Li, Dengsheng Lu, Yagang Lu, Guiying Li

“…Further research should focus on developing suitable approaches to enhance the FCH retrieval accuracy from spaceborne LiDAR data and integrating multi-source data and modeling algorithms to produce accurate wall-to-wall FCH distribution in a large area.…”
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SCCA-YOLO: Spatial Channel Fusion and Context-Aware YOLO for Lunar Crater Detection by Jiahao Tang, Boyuan Gu, Tianyou Li, Ying-Bo Lu

“…Experimental results demonstrate that our model achieves an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>m</mi><mi>A</mi><msub><mi>P</mi><mrow><mn>0.5</mn></mrow></msub></mrow></semantics></math></inline-formula> of 96.5% and an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>m</mi><mi>A</mi><msub><mi>P</mi><mrow><mn>0.5</mn><mo>:</mo><mn>0.95</mn></mrow></msub></mrow></semantics></math></inline-formula> of 81.5%, outperforming other mainstream detection models including the YOLO family of algorithms. These findings highlight the potential of SCCA-YOLO for high-precision lunar crater detection and provide valuable insights into future lunar surface analysis.…”
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Competence model scheming of the graduate as an assessment tool for the quality of education by E. N. Shaforostova, A. A. Valova

“…For reliable identification of the formation level of social and personal qualities, the obtained adapted version of R Ketell’s multifactorial questionnaire was used, in which the components are the formed groups of personal qualities. The algorithms of adaptive testing to assess the level of competence of students in the development of academic disciplines, as well as the assessment of existing social and personal qualities of students were developed.Conclusion. …”
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Fault diagnosis method of mine hoist main bearing with small sample based on VAE-WGAN by Fan JIANG, Hongyan SONG, Xi SHEN, Zhencai ZHU, Shuman CHENG

“…Furthermore, a fault diagnosis method based on CBAM-MobileNetV2 is proposed to achieve fault diagnosis of mine hoist main bearings under small sample data. At the algorithmic level, the Wasserstein distance metric is introduced to solve the problem of vanishing training gradients in generative adversarial networks. …”
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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

“…Downsampling and upsampling algorithms were applied to resample the spectral data at 5 cm and 40 cm resolutions, generating datasets that cover the entire range from 5 cm to 40 cm. …”
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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 estimation models for the SPAD values in different growth stages were, respectively, established through five machine learning algorithms: multiple linear regression (MLR), partial least squares regression (PLSR), support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost). …”
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Unveiling purine metabolism dysregulation orchestrated immunosuppression in advanced pancreatic cancer and concentrating on the central role of NT5E by Junqian Zhang, Xiaobo Zhang, Ruixin Wu, Chang-Sheng Dong

“…We quantitatively appraised the PM traits of diverse cell subsets via scoring algorithms such as AUCell and Ucell. Moreover, cell development and cell-cell interaction analysis elucidated the alterations in TME induced by PM dysregulation. …”
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Differential neuropilin isoform expressions highlight plasticity in macrophages in the heterogenous TME through in-silico profiling by Hyun-Jee Han, Marcos Rubio-Alarcon, Thomas Allen, Sunwoo Lee, Taufiq Rahman

“…Datasets were processed using established bioinformatics pipelines, including clustering algorithms, to determine cellular heterogeneity and quantify NRP isoform expression within distinct macrophage populations. …”
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A machine learning-based depression risk prediction model for healthy middle-aged and older adult people based on data from the China health and aging tracking study by Fang Xia, Jie Ren, Linlin Liu, Yanyin Cui, Yufang He

“…Several machine learning algorithms, including logistic regression, k-nearest neighbor, support vector machine, multilayer perceptron, decision tree, and XGBoost, were employed to predict the 2-year depression risk. …”
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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

“…We applied five machine learning algorithms—Random Forest, XGBoost, LightGBM, Stacking, and Convolutional Neural Network Transformers (CNNT)—and evaluated their performance using six metrics: R, RMSE, CSI, MAR, FAR, and fbias, on both validation and testing sets. …”
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Estimating Winter Canola Aboveground Biomass from Hyperspectral Images Using Narrowband Spectra-Texture Features and Machine Learning by Xia Liu, Ruiqi Du, Youzhen Xiang, Junying Chen, Fucang Zhang, Hongzhao Shi, Zijun Tang, Xin Wang

“…Subsequently, machine learning algorithms were applied to develop estimation models for winter canola biomass. …”
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The Role of AI in Nursing Education and Practice: Umbrella Review by Rabie Adel El Arab, Omayma Abdulaziz Al Moosa, Fuad H Abuadas, Joel Somerville

“…First, ethical and social implications were consistently highlighted, with studies emphasizing concerns about data privacy, algorithmic bias, transparency, accountability, and the necessity for equitable access to AI technologies. …”
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Pharmacological correction of hepatotoxicity induced by anti-tuberculosis drugs by D. S. Sukhanov, E. V. Timofeev, Y. S. Alekseeva, K. A. Nagornova

“…At the same time, there is no consistent understanding of their effectiveness, as well as consistent application algorithms, since a number of drugs have been studied only in experimental or small observational clinical studies. …”
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Construction and demolition waste material library based on vision systems dataZenodo by Maria Teresa Calcagni, Giovanni Salerno, Gloria Cosoli, Giuseppe Pandarese, Gian Marco Revel

“…In addition, the benefits of this resource for the scientific and industrial community are discussed, including the possibility of using the data to develop/fine-tune artificial intelligence (AI) algorithms capable of optimising sorting and recycling processes by recognition and discrimination among different types of CDW material using the aforementioned sensors. …”
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Prediction of outcomes following intravenous thrombolysis in patients with acute ischemic stroke using serum UCH-L1, S100β, and NSE: a multicenter prospective cohort study employin... by Ming-Ya Luo, Yang Qu, Peng Zhang, Reziya Abuduxukuer, Li-Juan Wang, Li-Chong Yang, Zhi-Guo Li, Xiao-Dong Liu, Ce Han, Dan Li, Wei-Jia Wang, Dian-Ping Lv, Ming Liu, Jian Gao, Jing Xu, Yongfei Jiang, Hai-Nan Chen, Fu-Jin Li, Li-Ming Sun, Qi-Dong Sun, Yingbin Qi, Si-Yin Sun, Yu Zhang, Zhen-Ni Guo, Yi Yang

“…Least Absolute Shrinkage and Selection Operator regression was used for feature selection, and six ML algorithms were tested. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), F 1-score, calibration curve, and decision curve analysis. …”
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Expectations and Requirements of Surgical Staff for an AI-Supported Clinical Decision Support System for Older Patients: Qualitative Study by Adriane Uihlein, Lisa Beissel, Anna Hanane Ajlani, Marcin Orzechowski, Christoph Leinert, Thomas Derya Kocar, Carlos Pankratz, Konrad Schuetze, Florian Gebhard, Florian Steger, Marina Liselotte Fotteler, Michael Denkinger

“…These challenges and demands have led to the SURGE-Ahead project that aims to develop a clinical decision support system (CDSS) for geriatric comanagement in surgical clinics including a decision support for the best continuity of care option, supported by artificial intelligence (AI) algorithms. ObjectiveThis qualitative study aims to explore the current challenges and demands in surgical geriatric patient care. …”
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Predictive performance of risk prediction models for lung cancer incidence in Western and Asian countries: a systematic review and meta-analysis by Yah Ru Juang, Lina Ang, Wei Jie Seow

“…In addition, 14.8% (8/54) of the studies directly compared biomarker-based models with those incorporating only traditional risk factors, demonstrating improved discrimination. Machine-learning algorithms were applied in eight Western models and two Asian models. …”
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Estrategia de control para robots manipuladores con realimentación visual y plataforma electro-neumática de 3gdl // Control Scheme for robots manipulators visual servoingand 3DOF e... by René González-Rodríguez, Luís Hernández-Santana, Eduardo Izaguirre, Ernesto Rubio

“…The control scheme presented opens a new research field in the task space control with algorithms for the solution of, trajectory control and feed-forward control.…”
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Explainable Artificial Intelligence Driven Segmentation for Cervical Cancer Screening by Niruthikka Sritharan, Nishaanthini Gnanavel, Prathushan Inparaj, Dulani Meedeniya, Pratheepan Yogarajah

“…This innovative approach to segmentation is formally introduced through two algorithms detailed in this paper. The weakly supervised segmentation framework achieved a Dice Similarity Coefficient (DSC) of 62.05% and an Intersection over Union (IoU) of 61.89%. …”
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A Transcriptomic Biomarker for Predicting the Response to TACE Correlates with the Tumor Microenvironment and Radiomics Features in Hepatocellular Carcinoma by Wang C, Leng B, You R, Yu Z, Lu Y, Diao L, Jiang H, Cheng Y, Yin G, Xu Q

“…Differentially expressed gene analysis and machine learning algorithms were used to identify genes for constructing the TACE failure signature (TFS). …”
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