Computational Techniques for Analysis of Thermal Images of Pigs and Characterization of Heat Stress in the Rearing Environment by Maria de Fátima Araújo Alves, Héliton Pandorfi, Rodrigo Gabriel Ferreira Soares, Gledson Luiz Pontes de Almeida, Taize Calvacante Santana, Marcos Vinícius da Silva

“…The image analysis consisted of its pre-processing, followed by color segmentation to isolate the region of interest and later the extraction of the animal’s surface temperatures, from a developed algorithm and later the recognition of the comfort pattern through machine learning. The results indicated that the automated color segmentation method was able to identify the region of interest with an average accuracy of 88% and the temperature extraction differed from the Therma Cam program by 0.82 °C. …”
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AI Functionalities in Cobot-Based Manufacturing for Performance Improvement in Quality Control Application by Madis Moor, Martinš Sarkans, Tavo Kangru, Tauno Otto, Jüri Riives

“…Artificial intelligence (AI) and Machine Learning (ML) are the technologies that make machines capable of making human-like decisions. …”
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Unveiling the mechanisms and promising molecular targets of curcumin in pancreatic cancer through multi-dimensional data by HongMing Xie, JieBin Liang, HongBiao He, Zewei Zhuo, JiaXuan Li

“…Clustering analysis categorized PC samples into four distinct subgroups: C1 and CII, which showed high expression and elevated immune cell infiltration, and C2 and CI, which exhibited the opposite pattern. Significant variations in scores of DEHG were seen between C1 and C2, in addition to between CI and CII. …”
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Breast cancer survival prediction using an automated mitosis detection pipeline by Nikolas Stathonikos, Marc Aubreville, Sjoerd deVries, Frauke Wilm, Christof A Bertram, Mitko Veta, Paul J vanDiest

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Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer by Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang

“…Abstract This study aimed to develop an interpretable machine learning model that accurately predicts Ki-67 expression in breast cancer (BC) patients using a combination of dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI) radiomics and clinical-imaging features. …”
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Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method by Fachri Ayudi Fitrony, Laksmita Dewi Supraba, Tessa Rantung, I Made Artha Agastya, Kusrini Kusrini

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FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging by Abhilasha Dave, Cong Wang, James Russell, Ryan Herbst, Jana Thayer

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Artificial Intelligence Approach in Hip Prosthesis Identification and Addressing Radiographic Outcome Measures by Omar Musbahi, MSc, ChM, Savvas Hadjixenophontos, MEng, Saran S. Gill, Iris Soteriou, Bsc, Kyriacos Pouris, Bsc, Takuro Ueno, PhD, Justin P. Cobb, MCh

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Contrasting spatial variations between above and below-ground net primary productivity in global grasslands by Ying Hu, Yue Yang, Yu Wei, Xiaozhen Li, Yue Jiao, Jiapei Liao, Ruiyu Fu, Lichong Dai, Zhongmin Hu

“…However, the spatial pattern and influencing factors of NPP and its components, especially the belowground net primary productivity (BNPP) remain unclear. …”
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Enhancing the Accuracy of Land Use/Cover Map Using Some Spectral Indices in Sarab County–East Azerbaijan by A. Sarabchi, H. Rezaei, F. Shahbazi

“…Subsequently, the LULC pattern in the study area was classified using the RGB+NIR+SWIR1 bands of Landsat 8, employing both SVM and maximum likelihood classifiers. …”
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MNEMOSINE: A Modular Framework to Monitor Interaction in Multimodal Interactive Spaces by Fabio Barros, Bernardo Marques, Antonio Teixeira, Samuel Silva

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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…The growing availability of wearable devices capable of real-time HRV data collection opens up opportunities for early detection and health status classification using machine learning. ObjectiveThis study aimed to identify HRV patterns capable of distinguishing individuals with active COVID-19 and post–COVID-19 condition and healthy controls using data collected from wearable devices and processed using machine learning models. …”
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A Data-Driven Approach for Predicting Remaining Useful Life of Semiconductor Devices Based on Machine Learning and Synthetic Data Generation: A Review and Case Study on SiC MOSFETs by Yarens J. Yarenscruz, Fernando Castano, Alberto Villalonga, Madhav Mishra, Rodolfo E. Haber

“…Data-driven approaches, particularly those methods based on machine learning, are currently being used due to their ability to model complex degradation patterns without the need for explicit physical modeling. …”
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Psychotherapist remarks’ ML classifier: insights from LLM and topic modeling application by Alexander Vanin, Vadim Bolshev, Anastasia Panfilova

“…IntroductionThis paper addresses the growing intersection of machine learning (ML) and psychotherapy by developing a classification model for analyzing topics in therapist remarks. …”
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Temporal and Spatial Dynamics of Dust Storms in Uzbekistan from Meteorological Station Records (2010–2023) by Natella Rakhmatova, Bakhriddin E. Nishonov, Lyudmila Shardakova, Albina Akhmedova, Alisher Khudoyberdiev, Valeriya Rakhmatova, Dmitry A. Belikov

“…This study highlights the importance of regional wind patterns and geomorphology in SDS formation, with prevailing wind directions from the northwest, west, and south. …”
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IDEEA: information diffusion model for integrating gene expression and EEG data in identifying Alzheimer’s disease markers by Enes Ozelbas, Tuba Sevimoglu, Tamer Kahveci

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Causal Discovery Analysis Reveals Global Sources of Predictability for Regional Flash Droughts by Sudhanshu Kumar, Di Tian

“…CENs revealed that the Indian Ocean Dipole, Pacific North Atlantic patterns, Bermuda high‐pressure system, and teleconnection patterns via Rossby wave train and jet streams strongly influence FDs in these regions. …”
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ICARus: a pipeline to extract robust gene expression signatures from transcriptome datasets by Zhaorong Li, Juan I. Fuxman Bass, Juan I. Fuxman Bass, Juan I. Fuxman Bass, Juan I. Fuxman Bass

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Integrated Hyperparameter Optimization with Dimensionality Reduction and Clustering for Radiomics: A Bootstrapped Approach by S. J. Pawan, Matthew Muellner, Xiaomeng Lei, Mihir Desai, Bino Varghese, Vinay Duddalwar, Steven Y. Cen

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Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis by Asif Rahman, Maqsood Hayat, Nadeem Iqbal, Fawaz Khaled Alarfaj, Salem Alkhalaf, Fahad Alturise

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