Transferring Face Recognition Techniques to Entomology: An ArcFace and ResNet Approach for Improving Dragonfly Classification by Zhong Li, Shaoyan Pu, Jingsheng Lu, Ruibin Song, Haomiao Zhang, Xuemei Lu, Yanan Wang

“…The model is mainly built based on the classic face recognition algorithm (ResNet50+ArcFace), and ResNet50 is used as the comparison algorithm for model performance. …”
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Advancing Alzheimer's Therapy: Computational strategies and treatment innovations by Jibon Kumar Paul, Abbeha Malik, Mahir Azmal, Tooba Gulzar, Muhammad Talal Rahim Afghan, Omar Faruk Talukder, Samar Shahzadi, Ajit Ghosh

“…Through computational simulations, researchers can predict drug efficacy, optimize lead compounds, and facilitate personalized medicine approaches. …”
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Identification and multi-omics analysis of essential coding and long non-coding genes in colorectal cancer by Yanguo Li, Zixing Meng, Chengjiang Fan, Hao Rong, Yang Xi, Qi Liao

“…Then, 29 essential long non-coding genes (ESLs) were predicted using Hypergeometric Test (HT) and Personalized PageRank (PPR) algorithms based on ESPs and co-expressed network constructed from scRNA-seq. …”
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3D Reconstruction and Deformation Detection of Rescue Shaft Based on RGB-D Camera by Hairong Gu, Bokai Liu, Lishun Sun, Mostak Ahamed, Jia Luo

“…The method also provides deformation profiles and accessibility predictions, with diameter estimates ranging from 510 mm to 540 mm, enabling accurate assessments of shaft usability and deformation trends. …”
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A Resting ECG Screening Protocol Improved with Artificial Intelligence for the Early Detection of Cardiovascular Risk in Athletes by Luiza Camelia Nechita, Dana Tutunaru, Aurel Nechita, Andreea Elena Voipan, Daniel Voipan, Anca Mirela Ionescu, Teodora Simina Drăgoiu, Carmina Liana Musat

“…Statistical methods were used to examine each sport’s specific cardiovascular adaptations and classify cardiovascular risk predictions as low, moderate, or high risk. <b>Results:</b> The accuracy, sensitivity, specificity, and precision of the AI system were 97.87%, 75%, 98.3%, and 98%, respectively. …”
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Inflammation-Mediated Regulation of MicroRNA Expression in Transplanted Pancreatic Islets by Valia Bravo-Egana, Samuel Rosero, Dagmar Klein, Zhijie Jiang, Nancy Vargas, Nicholas Tsinoremas, Marco Doni, Michele Podetta, Camillo Ricordi, R. Damaris Molano, Antonello Pileggi, Ricardo L. Pastori

“…The association between these miRNAs and mRNA target-predicting algorithms in genome-wide RNA studies of β-cell inflammation identified 238 potential miRNA gene targets. …”
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Using Neural Networks to Automate the Identification of Brightest Cluster Galaxies in Large Surveys by Patrick Janulewicz, Tracy M. A. Webb, Laurence Perreault-Levasseur

“…Training on simulations yields a squared correlation coefficient, R ^2 , between predictions and ground truth of R ^2  ≈ 0.94 when testing on simulations, which decreases to R ^2  ≈ 0.60 when testing on real data owing to discrepancies between data sets. …”
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Congo red fluorescence enhances digital pathology workflow in cardiac amyloidosis by Giorgio Cazzaniga, Monica De Gaspari, Vincenzo L’Imperio, Carlo Beretta, Angela Greco, Stefania Rizzo, Cristina Basso, Fabio Pagni

“…AI achieved an AUC-ROC of 0.87, 0.86 and 0.79 on the training, validation and test set, respectively, in tile-level classification for amyloidosis positivity and IoU and Dice scores indicating partial but reasonable overlap between predictions and ground truth in amyloid segmentation. …”
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Evaluation and Early Detection of Downy Mildew of Lettuce Using Hyperspectral Imagery by Songtao Ban, Minglu Tian, Dong Hu, Mengyuan Xu, Tao Yuan, Xiuguo Zheng, Linyi Li, Shiwei Wei

“…Moreover, regression models developed using Partial Least Squares (PLS), Random Forest (RF), and Convolutional Neural Network (CNN) algorithms demonstrated high accuracy and reliability in predicting DI, flavonoids, and anthocyanins, with the highest R² of 0.857, 0.910, and 0.963, respectively. …”
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Multigoal-oriented a posteriori error control for heated material processing using a generalized Boussinesq model by Beuchler, Sven, Endtmayer, Bernhard, Lankeit, Johannes, Wick, Thomas

“…Therein, error reductions and effectivity indices are consulted to establish the robustness and efficiency of our framework.…”
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Asymptomatic elevation of serum aminotransferase activity: stages of diagnostic search by Yu. A. Tereshchenko, S. Yu. Tereshchenko

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Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing by Zehua Wang, Zhongxiao Zhang

“…Five hub genes (CDKN2A, VIM, TGFB1, CTSS, and CDC20) were biomarkers with area under the curve (AUC) values > 0.8, indicating high predictive performance. In vitro validation experiments demonstrated that the expressions of all five biomarkers in KIRC cells were elevated, and the knockdown of CTSS could inhibit the migration and invasion of KIRC cells. …”
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Scenario Modelling for Reproducing Investment Potential of Institutional Sectors in the Regions of the Siberian Federal District by I. V. Naumov, A. V. Trynov, A. O. Safonov

“…This model suggests systems of predictive scenarios for the reproduction and choosing the optimal one to achieve positive dynamics of the socio-economic development of the regions. …”
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Identification of exosome-related genes associated with prognosis and immune infiltration features in pancreatic cancer by Jie Wang, Ming Qing, Jie Gui, Pingyong Zhong, Hao Hua

“…An ERG_score was developed for forecasting overall survival and its predictive capacity was confirmed in PC cases. A precise nomogram was established to enhance the clinical utility of the ERG_score. …”
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Association of MTHFR Polymorphisms with H-Type Hypertension: A Systemic Review and Network Meta-Analysis of Diagnostic Test Accuracy by Yixuan Kong, Jinghui Zheng, Lijuan Li, Liying Lu, Jie Wang

“…The present result suggests that MTHFR C667T rs1801133 polymorphism is associated with H-HTN risk and may act as a promising predictive biomarker for H-HTN risk. However, further well-designed studies are warranted to confirm these results.…”
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Integrating taxonomic and phenotypic information through FISH-enhanced flow cytometry for microbial community dynamics analysis by Valérie Mattelin, Josefien Van Landuyt, Frederiek-Maarten Kerkhof, Yorick Minnebo, Nico Boon

“…As a reference to correlate increased distinction with the incorporation of taxonomic information, 16S rRNA gene sequencing was used. Finally, a predictive algorithm was trained to correctly classify samples in the differently treated groups. …”
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Modeling and optimization of culture media for recombinant Helicobacter pylori vaccine antigen HpaA by Runqing Tan, Song Zhou, Min Sun, Yu Liu, Xiumei Ni, Jin He, Gang Guo, Kaiyun Liu

“…The artificial neural network linked genetic algorithm (ANN-GA) model exhibited superior predictive accuracy, achieving a rHpaA yield of 0.61 g/L, which represents a 93.2% increase compared to the initial medium. …”
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Parameter Sensitivity Analysis and Irrigation Regime Optimization for Jujube Trees in Arid Regions Using the WOFOST Model by Shihao Sun, Yingjie Ma, Pengrui Ai, Ming Hong, Zhenghu Ma

“…In this regard, the use of crop models can compensate for time-consuming and costly field trials to screen for better irrigation regimes, but their predictive accuracy is often compromised by parameter uncertainty. …”
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Prognostic value of gene signatures and proliferation in lymph-node-negative breast cancer. by Kristin Jonsdottir, Jörg Assmus, Aida Slewa, Einar Gudlaugsson, Ivar Skaland, Jan P A Baak, Emiel A M Janssen

“…<h4>Introduction</h4>The overall survival rate is good for lymph-node-negative breast cancer patients, but they still suffer from serious over- and some undertreatments. Prognostic and predictive gene signatures for node-negative breast cancer have a high number of genes related to proliferation. …”
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The signature based on interleukin family and receptors identified IL19 and IL20RA in promoting nephroblastoma progression through STAT3 pathway by Chen Ding, Hongjie Gao, Liting Zhang, Zhiyi Lu, Bowen Zhang, Ding Li, Fengyin Sun

“…The prognostic model incorporating these five genes demonstrated robust predictive power in both training and validation cohorts. …”
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