A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection by K. Anup Kumar, C. Vanmathi

“…PCSN-Net outperforms various complex algorithms, including EfficientNet, DenseNet, and Inception-ResNet-V2, despite preserving effective training and inference times. …”
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Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning by Qiong Li, Hongde Liu

“…A comprehensive machine learning framework incorporating 101 algorithmic combinations across 10 survival modeling approaches, including random survival forests and ridge regression, was employed to develop a robust prognostic model. …”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…However, traditional monitoring methods have notable limitations: ground-based measurements are inefficient; remote-sensing interpretation is susceptible to terrain and spectral interference; and traditional algorithms exhibit an insufficient feature representation capability. …”
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A Versatile Gyro Inclinometer, Adaptive to the Borehole Trajectory, Based on a Uniaxial Angular Rate Sensor by Ya. I. Binder, I. A. Khazov

“…The properties of orientation errors are examined using linearization methods, integral calculus, fundamentals of the calculus of variations, and the theory of linear differential equations.Results. …”
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Numerical Modeling Tools and S-derivatives by Anatoly Nikolaevich Morozov

“…The constructions are algorithmic in nature and can be applied in numerically computer research of various relevant models.…”
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Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Seyedeh Zeinab Shogrkhodaei, Biswajeet Pradhan, Soo-Mi Choi

“…This research introduces a novel approach combining human-based metaheuristics—Teaching Learning Based Optimization (TLBO) and Cultural Algorithms (CA)—with non-parametric Decision Tree (DT) models. …”
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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…Applying the random forest method to classify predictions of adaptive responses based on climatic variables showed that all thermoregulatory, hormonal, biochemical, and hematological responses are important, except for urea and T₃ concentrations, which had negative importance values. We conclude that adaptation results from an integration between energy and lipid metabolism, renal function, hormonal profile, and thermoregulatory, hematological, and productive responses. …”
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Identifying Lactylation-related biomarkers and therapeutic drugs in ulcerative colitis: insights from machine learning and molecular docking by Yao Yang, Xu Sun, Bin Liu, Yunshu Zhang, Tong Xie, Junchen Li, Jifeng Liu, Qingkai Zhang

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METHOD AND SYSTEM FOR ASSESSING OF SPORTSMAN’S PHYSIOLOGICAL RESERVES DURING PHYSICAL EXERCISES by Nguyen Mau Thach, Nguyen Trong Tuyen, Tran Trong Huu

“…The circle diagram is proposed for taking into account of all mentioned parameters and its variation dynamics. The value of the integral PR parameter is an area of a polygon, which is obtained on the circle diagram using normalized values of the diagnostically significant parameters. …”
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Plot-Rice v1.0: A global plot-based rice benchmark dataset with spatiotemporal heterogeneity for scientific deep learning by Ji Ge, Hong Zhang, Wenjiang Huang, Zihuan Guo, Lu Xu, Yazhe Xie, Mingyang Song, Yinhaibin Ding, Chao Wang

“…The absence of a global, standardized satellite dataset for rice mapping benchmarking has long resulted in both substantial redundant data processing efforts and challenges in evaluating new algorithms under a unified benchmark. To address these deficiencies, this paper introduces Plot-Rice v1.0, a global heterogeneous rice benchmark dataset based on Sentinel-1 and Sentinel-2 images, along with an automated framework that integrates SAR temporal features and leverages the foundation image segmentation model SAM-2 to generate plot-level rice samples. …”
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Machine Learning Model Coupled with Graphical User Interface for Predicting Mechanical Properties of Flax Fiber by T. Nageshkumar, Prateek Shrivastava, L. Ammayapan, Manisha Jagadale, L. K. Nayak, D. B. Shakyawar, Indran Suyambulingam, P. Senthamaraikannan, R. Kumar

“…In this study, a total of 432 patterns of input and output parameters obtained from laboratory experiments were used to develop machine learning algorithms (Random forest, support vector, and XGBoost). …”
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Supply chain management and optimization in transportation logistics by Saoussen Krichen

“…<p>Supply chain management (SCM) is the decision-making process that steers numerous activities in order to generate added values for all stakeholders. The aim of this process is to optimize each activity in terms of advantageous profits to the suppliers, retailers and customers. …”
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Of cattle and feasts: Multi-isotope investigation of animal husbandry and communal feasting at Neolithic Makriyalos, northern Greece. by Petra Vaiglova, Paul Halstead, Maria Pappa, Sevi Triantaphyllou, Soultana M Valamoti, Jane Evans, Rebecca Fraser, Panagiotis Karkanas, Andrea Kay, Julia Lee-Thorp, Amy Bogaard

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A Nondestructive Detection Method for the Muti-Quality Attributes of Oats Using Near-Infrared Spectroscopy by Linglei Li, Long Li, Guoyuan Gou, Lang Jia, Yonghu Zhang, Xiaogang Shen, Ruge Cao, Lili Wang

“…Subsequently, the optimal PLS model was obtained by integrating feature wavelength selection algorithms (CARS, SPA, UVE, LAR). …”
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Development and validation of a radiomics-based nomogram for predicting pathological grade of upper urinary tract urothelial carcinoma by Yanghuang Zheng, Hongjin Shi, Shi Fu, Haifeng Wang, Xin Li, Zhi Li, Bing Hai, Jinsong Zhang

“…Both LR and ML algorithms were utilized to develop predictive models. …”
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Clinical Validation of a Machine Learning-Based Biomarker Signature to Predict Response to Cytotoxic Chemotherapy Alone or Combined with Targeted Therapy in Metastatic Colorectal C... by Duilio Pagano, Vincenza Barresi, Alessandro Tropea, Antonio Galvano, Viviana Bazan, Adele Caldarella, Cristina Sani, Gianpaolo Pompeo, Valentina Russo, Rosa Liotta, Chiara Scuderi, Simona Mercorillo, Floriana Barbera, Noemi Di Lorenzo, Agita Jukna, Valentina Carradori, Monica Rizzo, Salvatore Gruttadauria, Marco Peluso

“…Various machine learning algorithms, like random survival forest and neural networks, will be integrated to develop a highly accurate and stable predictive model. …”
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Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning by Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng

“…This study accurately inverts key growth parameters of rice, including Leaf Area Index (LAI), chlorophyll content (SPAD) value, and height, by integrating multisource remote sensing data (including MODIS and ERA5 imagery) and deep learning models. …”
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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

“…In addition, both MODIS and VIIRS have a large proportion of zero-valued pixels (volumetric and geometric-optical parameter layers), whereas the spatiotemporal distribution of zero-valued pixels in VIIRS is more widespread. …”
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A Robust Multispectral Reconstruction Network from RGB Images Trained by Diverse Satellite Data and Application in Classification and Detection Tasks by Xiaoning Zhang, Zhaoyang Peng, Yifei Wang, Fan Ye, Tengying Fu, Hu Zhang

“…However, the relatively high cost of multispectral sensors and lower spatial resolution limit the widespread application of multispectral data, and existing reconstruction algorithms suffer from a lack of diverse training datasets and insufficient reconstruction accuracy. …”
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Study on a Traditional Chinese Medicine constitution recognition model using tongue image characteristics and deep learning: a prospective dual-center investigation by Yongyue Liu, Linmiao Fan, Mei Zhao, Dongshen Wei, Menglan Zhao, Yihang Dong, Xiaoqing Zhang

“…Eight machine learning algorithms were employed to construct and evaluate the efficacy of the models. …”
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