Enhanced diabetes prediction using skip-gated recurrent unit with gradient clipping approach by Suhas Kamshetty Chinnababu, Suhas Kamshetty Chinnababu, Suhas Kamshetty Chinnababu, Ananda Babu Jayachandra, Ananda Babu Jayachandra, Swathi Holalu Yogesh, Swathi Holalu Yogesh, Mohamed Abouhawwash, Mohamed Abouhawwash, Doaa Sami Khafaga, Eman Abdullah Aldakheel, Vinaykumar Vajjanakurike Nagaraju, Vinaykumar Vajjanakurike Nagaraju

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Pattern transition recognition based on transfer learning for exoskeleton across different terrains by Yifan Gao, Jianbin Zheng, Yang Gao, Ziyao Chen, Jing Tang, Liping Huang

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An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer by Lihuan Dai, Jinxue Yin, Xin Xin, Chun Yao, Yongfang Tang, Xiaohong Xia, Yuanlin Chen, Shuying Lai, Guoliang Lu, Jie Huang, Purong Zhang, Jiansheng Li, Xiangguang Chen, Xi Zhong

“…Here, we developed and validated an interpretable machine learning (ML) model based on contrast-enhanced computed tomography (CECT) radiomics for preoperatively predicting PD-L1 expression status in patients with gastric cancer (GC). …”
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Galaxy Morphology Classification via Deep Semisupervised Learning with Limited Labeled Data by Zhijian Luo, Jianzhen Chen, Zhu Chen, Shaohua Zhang, Liping Fu, Hubing Xiao, Chenggang Shu

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Topological characterization, computational, spectroscopic (FT-IR, 1H, 13C NMR) exploration, chemical reactivity analysis of 6-(3,3-dimethyl-oxiran-2-ylidene)-5,5-dimethyl-hex-3-en... by R. Mohamed Hisam, P. Rajesh, E. Dhanalakshmi, Jeffrin JA Laura, M. Prabhaharan, G. Jayaraman

“…The Electron Localization Function (ELF) and Localized Orbital Locator (LOL) analyses reveals details on electron distribution. Reduced Density Gradient (RDG) analysis provided insights into bonding and non-bonding interactions. …”
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A machine learning based radiomics approach for predicting No. 14v station lymph node metastasis in gastric cancer by Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Xiangli Li, Xiangchao Song, Xiangchao Song, Xiangchao Song, Xiangchao Song, Lingwei Wang, Lingwei Wang, Lingwei Wang, Lingwei Wang, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye

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New indicator species for associations within mesotrophic oak-hornbeam forests in Poland by Grzegorz J. Wolski, Zbigniew Celka, Jolanta Marciniuk, Paweł Marciniuk, Józef Mitka, Sławomir Nowak, Renata Afranowicz-Cieślak, Andrzej Kruk, Andrzej Łysko, Agnieszka Popiela

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Interpretable Machine Learning for Serum-Based Metabolomics in Breast Cancer Diagnostics: Insights from Multi-Objective Feature Selection-Driven LightGBM-SHAP Models by Emek Guldogan, Fatma Hilal Yagin, Hasan Ucuzal, Sarah A. Alzakari, Amel Ali Alhussan, Luca Paolo Ardigò

“…Serum samples underwent liquid and gas chromatography–time-of-flight mass spectrometry (LC-TOFMS and GC-TOFMS). Mutual Information (MI), Sparse Partial Least Squares (sPLS), Boruta, and Multi-Objective Feature Selection (MOFS) approaches were applied to the data for biomarker discovery. …”
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The Sulfate-Rich and Extreme Saline Sediment of the Ephemeral Tirez Lagoon: A Biotope for Acetoclastic Sulfate-Reducing Bacteria and Hydrogenotrophic Methanogenic Archaea by Lilia Montoya, Irma Lozada-Chávez, Ricardo Amils, Nuria Rodriguez, Irma Marín

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Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Canc... by Cemil Colak, Fatma Hilal Yagin, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

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