Geometric Alignment Improves Wheat NDVI Calculation from Ground-Based Multispectral Images by Md Asrakul Haque, Md Nasim Reza, Md Rejaul Karim, Md Razob Ali, Samsuzzaman, Kyung-Do Lee, Yeong Ho Kang, Sun-Ok Chung

“…The results showed that proper FOV alignment significantly improved regression metrics (R² and RMSE) at all growth stages, with R² improvements ranging from 3% to 33%, and RMSE reductions from 0.03 to 0.06, respectively. …”
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Incidence of surgical site infections and prediction of risk factors in a hospital center in Morocco by Rachid Flouchi, Mohamed El Far, Abdelaziz Hibatallah, Abderrahim Elmniai, Ibtissam Rhbibou, Ibrahim Touzani, Naoufal El Hachlafi, Kawtar Fikri-Benbrahim

“…The SSIs’ risk factors were assessed by univariate statistical analysis and logistic regression using the Scikit Learn function of Python. Results: The average age of the studied population was 35 ± 1 years. …”
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Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG by Thais de Andrade Silva, Gabriel Fernandes Souza dos Santos, Adilson Ribeiro Prado, Daniel Cruz Cavalieri, Arnaldo Gomes Leal Junior, Flávio Garcia Pereira, Camilo A. R. Díaz, Marco Cesar Cunegundes Guimarães, Servio Túlio Alves Cassini, Jairo Pinto de Oliveira

“…The comprehensive database utilized Raman spectra from all 594 blood serum samples. Machine learning investigations were carried out using the Scikit-Learn library and were implemented in Python, and the characteristics of Raman spectra of positive and negative SARS-CoV-2 samples were extracted using the Uniform Manifold Approximation and Projection (UMAP) technique. …”
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Comparative Study between Platelet-rich Plasma and Platelet-rich Plasma with Hyaluronic Acid in Knee Osteoarthritis Population by Tilakraj Kulandaivel, Prabhu Angamuthu Nagarajan, Girish Muppala, Uganath Subash Boominathan, Rukhaiya Fathima

“…Conversely, in the PRP alone group, 70% (35 cases) demonstrated fair outcomes, whereas 30% (15 cases) showed poor outcomes. Employing the Python formula, we calculated a <italic>p</italic>-value of 0.002, elucidating the significance of our results. …”
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Implementing intelligent nursing interventions to enhance self-efficacy and hospital readiness in parents of preterm infants: a randomised controlled trial protocol by Hong Zhang, Kang Lin, Shaoyan Zhang, Zhihan Zhang, Wenxia Zheng, Zhenyu Chen, Zibin Lin, Niyang Lin

“…Informed consent is required from all participants or their guardians. The authors intend to submit their findings for publication in peer-reviewed journals or academic conferences.Trial registration number NCT06635473.…”
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Performance Analysis of Artificial Intelligence Models for Classification of Transmission Line Losses by Abraham O. Amole, Oluwagbemiga E. Ajiboye, Stephen Oladipo, Ignatius K. Okakwu, Ibrahim A. Giwa, Olamide O. Olusanya

“…It also supports the realization of SDG 7 by aiming to provide access to reliable, affordable, and sustainable energy for all.…”
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Enhancing Nature Engagement through Mobile Applications: A Technological Approach by Alwinfernandez Sandanasamy, Sumendra Yogarayan, Siti Fatimah Abdul Razak, Jonathan Freddie Sandanasamy, Afizan Azman

“…The application also acts as a one-stop shop for gardening tools, which eases human interaction with nature. All these features are made together with offering accessibility as a focus. …”
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Modeling and simulation of optical wireless communication channels in IoUT considering water types turbulence and transmitter selection by M. Mokhtar Zayed, Mona Shokair

“…Simulation models are developed and implemented using MATLAB and Python to analyze key parameters such as transmission distance, water type, transmitter characteristics, wavelength, and turbulence intensity. …”
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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…Introduction. All polymer materials and composites based on them are characterized by pronounced rheological properties, the prediction of which is one of the most critical tasks of polymer mechanics. …”
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A Cross-sectional Study on Stature Estimation from Arm Lengths among North Indian Population using Machine Learning by Arunima Dutta, Gyamar Anya

“…All the measurements were statistically significant, with p-values <0.001. …”
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Option Pricing Based on Modular Neural Network by Moslem Peymany Foroushani, mohamad ali dehghan dehnavi, Milad Kouhkan

“…In the neural network models, option prices were predicted using Python and its machine learning algorithms. Finally, the predicted prices from the models were compared with the market prices of the same options. …”
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Epidemiologia de lesões em jovens atletas de futebol das categorias sub-17 e 20 de um clube profissional de futebol do Rio de Janeiro by Vicente Pinheiro Lima, Rodrigo Gomes de Souza Vale, Bruno Lucas Pinheiro Lima, Gilson Ramos de Oliveira Filho, Juliana Brandão Pinto de Castro, Jefferson da Silva Novaes, Rodolfo de Alkmim Moreira Nunes

“…Os dados foram analisados na linguagem de programação Python 2.7, na interface gráfica Spyder 3.3.1, com o uso do programa gráfico Anaconda. …”
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Spatial Downscaling of Soil Moisture Product to Generate High-Resolution Data: A Multi-Source Approach over Heterogeneous Landscapes in Kenya by Asnake Kassahun Abebe, Xiang Zhou, Tingting Lv, Zui Tao, Abdelrazek Elnashar, Asfaw Kebede, Chunmei Wang, Hongming Zhang

“…Moreover, the performance of FLDAS and its downscaled version across all climate zone is consistent. Despite the uncertainties among the datasets, the framework effectively improved the representation of SM variability spatiotemporally. …”
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Versatile machine learning algorithms for FTIR spectroscopy: differentiating crosslinked and non-crosslinked gelatin samples by Juliana Rincón-López, Eliana Álvarez-Valdés, Daniela Velez-Arango, Estefanía Rojas Zuleta, Leidy Yuliana Vargas Soto, Liliana Lellesch, Victor Alonso García Londoño, Milton Rosero-Moreano, Gonzalo Taborda-Ocampo

“…For the FTIR results, machine learning classification models developed in the Python language were used to distinguish between cross-linked and non-cross-linked gelatin samples and two dimensionality reduction techniques (PCA, PLS) and four classification models (NCA-KNN, SVM, LDA, DT) were incorporated, all effectively classifying spectra across gelatin types in adjustment, training, test stages, and predictions, with higher precision observed for gelatins A, C, and D. …”
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Clinical Presentations and Treatment Approaches in a Retrospective Analysis of 128 Intracranial Arteriovenous Malformation Cases by Corneliu Toader, Mugurel Petrinel Radoi, Milena-Monica Ilie, Razvan-Adrian Covache-Busuioc, Vlad Buica, Luca-Andrei Glavan, Christian-Adelin Covlea, Antonio Daniel Corlatescu, Horia-Petre Costin, Carla Crivoi, Leon Danaila

“…Only four in-hospital deaths occurred, all in patients who underwent open surgery, and no deaths were recorded during the two-year follow-up. …”
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Exploring the patterns in traditional Chinese medicine for bipolar disorder: a data-driven network approach by Zhenshan Sun, Zhenshan Sun, Jiangbangrui Chu, Jiangbangrui Chu, Junjie Peng, Kefan Hu, Zhengyi Wang, Zhu Zhang, Ken Kin Lam Yung

“…Active botanical drugs were extracted from the BATMAN-TCM 2.0 database. All terms for botanical drugs and diseases were confirmed via the Pharmacopoeia of the People’s Republic of China 2020 Edition and Medical Subject Headings. …”
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Sentinel-2 Masking CNNs Trained on Physics-Supervised Labels by Efrain Padilla-Zepeda, Kevin Alonso, Raquel De Los Reyes, Deni Torres-Roman, Avi Putri Pertiwi, Tobias Storch

“…Rather than relying on manually labeled data, the proposed method selects high-quality training samples from Python-based atmospheric correction software (PACO), using pixel selection strategies to remove ambiguous or inconsistent labels. …”
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Remote monitoring of patients with obstructive sleep apnea syndrome treated with CPAP: a feasibility study by Amélie Hediger-Parolini, Florian Charbonnier, Stéphane Grandin, Hiromitsu Takahashi, Fabian Braun, Mathieu Lemay, Roger Hilfiker, Sandra Van den Broecke, Olivier Contal

“…Data synchronization and processing were conducted using a dedicated Python script. Primary outcomes included acceptability, compliance, autonomy in device usage, and data quality. …”
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AI-enhanced automation of building energy optimization using a hybrid stacked model and genetic algorithms: Experiments with seven machine learning techniques and a deep neural net... by Mohammad H. Mehraban, Samad ME Sepasgozar, Alireza Ghomimoghadam, Behrouz Zafari

“…Unlike the common practices, the scenario development and building optimization tend to be enhanced by using AI in the present paper, using a Python-based script alongside the Non-dominated Sorting Genetic Algorithm (NSGA-II) through EnergyPlus simulations. …”
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Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn’s disease by Zhuoyan Chen, Weimin Cai, Yuanhang He, Tianhao Mei, Yuxuan Zhang, Shiyu Li, Yiwen Hong, Yuhao Chen, Huiya Ying, Yuan Zeng, Fujun Yu

“…Twenty differential radiomics features were selected for integration into the ML models. All models demonstrated strong predictive performance in the validation cohort, with a mean area under the curve of 0.849. …”
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