CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer’s disease by Jingyuan Liu, Xiaojie Yu, Hidenao Fukuyama, Toshiya Murai, Jinglong Wu, Qi Li, Zhilin Zhang

“…Methods In this study, we proposed cross-scale equilibrium pyramid coupling (CSEPC), which is a novel diagnostic algorithm designed for small-sample multimodal medical imaging data. …”
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Integrin factor (FAM27E3), as a metastatic marker of papillary thyroid carcinoma, through the p53 signaling pathway promoting lymph node metastasis by Dong Zhang, Kai-Fang Xiang, Chen-Chen Hong, Xiao-Ping Bao, Yan Wu, Rui Wu

“…This study aims to explore the role and regulatory mechanism of the FAM27E3 in PTC lymph node metastasis.MethodThe seven thyroid cancer (THCA) datasets from the Gene Expression Omnibus (GEO) were combined as the training group, while the PTC dataset served as the testing group. …”
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CFD-based investigation of energy and exergy enhancement in a geothermal heat exchanger with hybrid nanofluid and novel turbulator by As'ad Alizadeh, Joy Djuansjah, Ali Basem, Aman Sharma, Muntadher Abed Hussein, Husam Rajab, Khalil Hajlaoui, R. Thakur

“…For λ = 2.55, φ = 3.5 %, and Re = 92,000, the Nusselt number increases by 52.78 %, while pressure drop rises by 65.77 % compared to the unmodified GHE. …”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…Then, a hybrid neural network is constructed by combining ANN and LSTM to capture nonlinear relationships and extract complex features, while the Transformer algorithm is introduced to capture global dependencies in high-dimensional feature space. …”
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Validation of Global Moderate-Resolution FAPAR Products over Boreal Forests in North America Using Harmonized Landsat and Sentinel-2 Data by Yinghui Zhang, Hongliang Fang, Zhongwen Hu, Yao Wang, Sijia Li, Guofeng Wu

“…To enhance the regional applicability of global FAPAR products, further algorithm improvements and expanded validation efforts are essential.…”
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Exploring the host response in infected lung organoids using NanoString technology: A statistical analysis of gene expression data. by Mostafa Rezapour, Stephen J Walker, David A Ornelles, Muhammad Khalid Khan Niazi, Patrick M McNutt, Anthony Atala, Metin Nafi Gurcan

“…IAV exerted a sustained impact on genes from the initial 24 hours, while PIV3 displayed a delayed yet substantial genomic response, suggestive of a gradual and nuanced strategy.…”
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ATP6AP1 drives pyroptosis-mediated immune evasion in hepatocellular carcinoma: a machine learning-guided therapeutic target by Lei Tang, Xiyue Wang, Zhengzheng Xia, Jiayu Yan, Shanshan Lin

“…Results Through a rigorous multi-algorithm screening process, ATP6AP1 was found to be a highly reliable biomarker with an area under the curve (AUC) of 0.979. …”
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A Deep Learning Method for Photovoltaic Power Generation Forecasting Based on a Time-Series Dense Encoder by Xingfa Zi, Feiyi Liu, Mingyang Liu, Yang Wang

“…In this study, we apply a deep learning algorithm, known as the time-series dense encoder (TiDE), which is an MLP-based encoder–decoder model, to forecast PV power generation. …”
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Pharmacoeconomic analysis of antiretroviral therapy regimes in the Syrian Arab Republic by Yu. Sh. Gushchina, А. Yu. Abramov, Y. J. Haitham

“…The average cost of the first prescribed regimen was 8,970.0 rubles/month, while the most expensive first-line regimens included a protease inhibitors class drug as the third component. …”
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Traditional and machine learning models for predicting haemorrhagic transformation in ischaemic stroke: a systematic review and meta-analysis by Yanan Wang, Zengyi Zhang, Zhimeng Zhang, Xiaoying Chen, Junfeng Liu, Ming Liu

“…Meta-analysis of 15 studies validating eight models showed a pooled area under the receiver operating characteristic curve of approximately 0.70 for predicting HT. Conclusion While significant progress has been made in developing HT prediction models, both traditional and machine learning-based models still have limitations in methodological rigour, predictive accuracy, and clinical applicability. …”
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Integrating structured and unstructured data for livestock price forecasting: a sustainability study from South Korea by Yifan Zhu, Yifan Zhu, Yifan Zhu, Tserenpurev Chuluunsaikhan, Jong-Hyeok Choi, Aziz Nasridinov

“…Additionally, we develop a Korean-language sentiment lexicon using an improved Term Frequency–Inverse Document Frequency (ITF-IDF) algorithm, enabling morpheme-level sentiment analysis for better sentiment extraction in Korean contexts. …”
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Emerging Healthcare Technologies in Gastrointestinal Endoscopy: 75 Years of Evolution by Irina Florina CHERCIU HARBIYELI, Elena Daniela BURTEA, Vlad IOVANESCU, Dan Nicolae FLORESCU, Ion ROGOVEANU, Dan Ionut GHEONEA, Adrian SAFTOIU

“…One of the most significant advancements is AI-driven endoscopy systems (EndoBrain, NvisionVLE, EndoAngel, GI Genius). Machine learning algorithms assist in real-time polyp detection, classification, and predictive analytics, enhancing diagnostic accuracy while reducing inter-observer variability and human error. …”
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Conventional scan body vs. scan bodies with auxiliary geometric devices: an in vitro study for edentulous full-arch implant impressions by Francesco Gianfreda, Carlo Raffone, Mirko Martelli, Alberto Pitino, Vito Carlo Alberto Caponio, Patrizio Bollero

“…Data were processed using Exocad and GOM Inspect Professional software, aligning scan body library files with mesh data using a best-fit algorithm. Angular, platform, and total deviations were calculated to assess positional trueness. …”
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Building a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel via the thermodynamic calculations and machine learning synergy by Shuaiwu Tong, Shuaijun Zhang, Chong Chen, Tao Jiang, Peng Li, Shizhong Wei

“…Furthermore, feature importance analysis, conducted using the Random Forest algorithm, revealed significant differences in the factors affecting sliding friction and abrasive wear. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. Regarding the Vis/NIR spectrophotometer dataset, good predictive performances were achieved for TSS (R² = 0.855) and DM (R² = 0.857), while the performance for TA was unsatisfactory (R² = 0.681). …”
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Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province by Yao Zhang, Qiao-Lin Wang, Wei Peng, Meng-Yuan Zhang, Yao Qin, Lun Zhang, Rong-Jie Wei, Dian-Ju Kang

“…The eXtreme Gradient Boosting (XGBoost) algorithm was employed to assess the influence of key environmental features, including precipitation, temperature, PM10, potential evaporation, vegetation cover, and NDVI, on BD incidence. …”
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Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images by Ke Zhang, Youhui Qiu, Songwei Feng, Han Yin, Qi Liu, Yuxin Zhu, Haoyu Cui, Xiaoying Wei, Guoqing Wang, Xiangxue Wang, Yang Shen

“…Results The UNet + + algorithm segmented tumor regions with 81.8% accuracy, 85.9% recall, 83.8% dice score and 68.3% IoU. …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…Here we propose a classical machine learning system, built around a Random Forest classifier paired with a novel feature extraction algorithm adapted from Explainable Boosted Linear Regression (EBLR). …”
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Penerapan Algoritma Fuzzy C Means untuk Analisis Permasalahan Simpanan Wajib Anggota Koperasi by Risma Rustiyan, Mustakim Mustakim

“…The development of cooperatives in Indonesia is currently quite rapid, On the data from Badan Pusat Statistik (BPS)  of the last 3 years updated on June 20, 2016 While mentioning the number of active cooperatives in Indonesia in 2015 as much as 150,223. …”
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The Core Mass Function across Galactic Environments. IV. The Galactic Center by Alva V. I. Kinman, Maya A. Petkova, Jonathan C. Tan, Giuliana Cosentino, Yu Cheng

“…The Brick has a Salpeter-like index α  = 1.28 ± 0.09, while the other regions have shallower indices: Sgr C has α  = 0.99 ± 0.06, and Sgr B2-DS has α  = 0.70 ± 0.03. …”
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