Adverse drug reaction assessment of pembrolizumab in cervical cancer treatment: a real-world pharmacovigilance study using the FAERS database by Huiping Zhang, Zhuo Zhou, Juan Wang, Shan Wang, Jie Ren, Ming Zhang, Mingyi Yang

“…ObjectiveAdvanced cervical cancer remains associated with high mortality rates. While pembrolizumab has improved clinical outcomes in cervical cancer, the therapeutic efficacy in advanced stages is often compromised by immune-related adverse events (irAEs). …”
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A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway by Jun-luan Mo, Xi Li, Lin Lei, Ji Peng, Xiong-shun Liang, Hong-hao Zhou, Zhao-qian Liu, Wen-xu Hong, Ji-ye Yin

“…We used machine learning algorithms to analyze small RNAs with significant differences between the two groups, fit the model through training sets, and optimize the model through testing sets. …”
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The Application of Mobile Devices for Measuring Accelerations in Rail Vehicles: Methodology and Field Research Outcomes in Tramway Transport by Michał Urbaniak, Jakub Myrcik, Martyna Juda, Jan Mandrysz

“…Future work will focus on optimizing the app’s data collection pipeline, refining standard-based analysis algorithms, and validating smartphone measurements against benchmark sensors.…”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. Specifically, an optimized You Only Look Once (YOLO) v8n model was developed by integrating a dilation-wise residual–dilated re-parameterization block module, a generalized feature pyramid network, and the Scylla Intersection-over-Union loss function. …”
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A method for high-accuracy localization of microseismic sources in mines based on finite element simulation by Dianyan NING, KaiPeng ZHU, Yongsheng ZHU, Shuxia YUAN, Zhenfang ZHOU

“…The results of this study provide a valuable reference for optimizing microseismic monitoring and early warning systems for mines.…”
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Identification of a Prognosis-Related Risk Signature for Bladder Cancer to Predict Survival and Immune Landscapes by Linhui Wang, Yutao Wang, Jianfeng Wang, Luanfeng Li, Jianbin Bi

“…Our findings provide a signature that might help determine the optimal treatment for individual patients with bladder cancer.…”
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Few-shot crop disease recognition using sequence- weighted ensemble model-agnostic meta-learning by Junlong Li, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang

“…Experimental results show that SWE-MAML demonstrates strong competitiveness compared to state-of-the-art algorithms on the PlantVillage dataset. Compared to the original MAML, SWE-MAML improves accuracy by 3.75%–8.59%. …”
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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

“…The results show that GEDI–FCH demonstrates better accuracy in plain and hill regions, while ICESat-2 ATLAS–FCH shows superior accuracy in the mountainous region. …”
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Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…In a subsequent step, Machine Learning (ML) algorithms are employed to classify these tumors as malign or benign cases. …”
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Monitoring and Comparative Analysis of NO₂ and HCHO in Shanghai Using Dual-Azimuth Scanning MAX-DOAS and TROPOMI by Hongmei Ren, Ang Li, Zhaokun Hu, Nannan Shao, Xinyan Yang, Hairong Zhang, Jiangman Xu, Jinji Ma

“…These findings not only reveal the spatiotemporal distribution characteristics of regional pollutants but optimize the sampling time and distance parameters for satellite–ground observation validation, providing data support for improving and enhancing the accuracy of satellite retrieval algorithms.…”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…Primary outcomes were in-hospital and ICU mortality, while 30-day and 90-day all-cause mortality served as secondary endpoints. …”
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Artificial intelligence (AI) in restorative dentistry: current trends and future prospects by Mariya Najeeb, Shahid Islam

“…Conclusion The review discussed trends, challenges, and future research directions in AI-driven dentistry, highlighting the transformative potential of AI in optimizing dental care. Key challenges include data privacy concerns, algorithmic bias, interpretability of AI decision-making processes, and the need for standardized AI training programs in dental education. …”
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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

“…Reinforcement Learning (RL) in CRs helps predict spectral changes and identify optimal transmission frequencies. This work presents the development of Deep RL (DRL) models for enhanced DSA in TV Whitespace (TVWS) cognitive radio networks using Deep Q-Networks (DQN) and Quantile-Regression (QR-DQN) algorithms. …”
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Predicting Olympic Medal Performance for 2028: Machine Learning Models and the Impact of Host and Coaching Effects by Zhenkai Zhang, Tengfei Ma, Yunpeng Yao, Ningjia Xu, Yujie Gao, Wanwan Xia

“…The proposed models, through an innovative integration of clustering, dimensionality reduction, and predictive algorithms, provide reliable forecasts and data-driven insights for optimizing national sports strategies. …”
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A Monocyte-Driven Prognostic Model for Multiple Myeloma: Multi-Omics and Machine Learning Insights by Xie L, Gao M, Tan S, Zhou Y, Liu J, Wang L, Li X

“…Subsequently, based on 482 prognostic moDEGs, we developed and validated an optimal model, termed the Monocyte-related Gene Prognostic Signature (MGPS), by integrating 101 predictive models generated from 10 machine learning algorithms across multiple transcriptome sequencing datasets. …”
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A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for lecanemab by Linlin Yan, Linhai Zhang, Zucai Xu, Zhong Luo

“…A biweekly 10 mg/kg was identified as the optimal therapeutic dosage. ARIA emerged as frequent treatment-related AEs, with APOEɛ4 carriers demonstrating heightened susceptibility. …”
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Unveiling PANoptosis in Acute Kidney Injury: An Integrative Multi-Dimensional Approach to Identify Key Biomarkers by Wang N, Zhang L, Xu Z, Xu Q, Lu Y, Niu P, Yan L, Wang L, Cao H, Shao F

“…Several machine learning algorithms were employed to determine the optimal feature genes. …”
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Classification of SERS spectra for agrochemical detection using a neural network with engineered features by Mateo Frausto-Avila, Monserrat Ochoa-Elias, Jose Pablo Manriquez-Amavizca, María del Carmen González-López, Gonzalo Ramírez-García, Mario Alan Quiroz-Juárez

“…Compared to other machine-learning algorithms, our approach offers reduced computational complexity while maintaining or exceeding the accuracy of more complex models. …”
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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…Abdominal fat (AF) in hens impacts egg production and may reflect poor feed efficiency, meaning that dynamic monitor of AF changes facilitate to optimize feeding management and production efficiency. …”
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Targeted urinary metabolomics combined with machine learning to identify biomarkers related to central carbon metabolism for IBD by Miao-Lin Lei, Guan-Wei Bi, Xiao-Lin Yin, Xiao-Lin Yin, Yue Wang, Yue Wang, Yue Wang, Zi-Ru Sun, Zi-Ru Sun, Zi-Ru Sun, Xin-rui Guo, Hui-peng Zhang, Xiao-han Zhao, Feng Li, Feng Li, Yan-Bo Yu

“…The optimal diagnostic model achieved a mean AUC of 0.84 for UC and 0.93 for CD. …”
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