Continuity of specialized care upon transfer of adolescents with epilepsy from a pediatric to adult outpatient service by M. N. Sarzhina, S. G. Burd, M. B. Mironov, M. M. Gunchenko, T. T. Batysheva

“…It is important to carefully watch any possible replacement of antiepileptic drugs (AEDs), which may affect the further course of epilepsy.Aim: to study the algorithms and procedures for bringing patients with epilepsy from a pediatric to adult outpatient practice, and also to evaluate the efficacy of therapy with synonymously replaced AEDs during this period.Materials and methods. …”
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An interpretable machine learning model for predicting early liver metastasis after pancreatic cancer surgery by Hao Zhu, Yiyan Zhou, Danyang Shen, Kejia Wu, Xiaojie Gan, Xiaofeng Xue, Weigang Zhang, Xiaohua Yang, Junyi Qiu, Ding Sun

“…Method This retrospective study included 407 pancreatic cancer patients who underwent surgery at the First Affiliated Hospital of Soochow University between January 2015 and December 2023, aiming to develop and validate a predictive model. Seven ML algorithms were employed to predict the risk of liver metastasis within one year after surgery. …”
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SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation by Brandon Theodorou, Anant Dadu, Mike Nalls, Faraz Faghri, Jimeng Sun

“…These models are computer algorithms that simulate how information changes. SECONDGRAM addresses data scarcity by generating realistic follow-up MRI imaging features, thereby enriching limited datasets. …”
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Safety assessment of deutetrabenazine: real-world adverse event analysis from the FAERS database by Yanping Shu, Yuanhe Wang, Jiaoying Liu, Lingyan Hu, Sichao Tong, Gang Wu, Xianlin Zhu

“…We eventually identified 100 valid PTs that met the criteria of the four algorithms. Drug ineffective, dyskinesia, depression, somnolence, suicidal ideation were considered to be the common PTs of deutetrabenazine. …”
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Comparison and Evaluation of Rain Gauge, CMORPH, TRMM PR and GPM DPR KuPR Precipitation Products over South China by Rui Wang, Huiping Li, Hao Huang, Liangliang Li

“…This study aims to provide valuable insights for enhancing precipitation retrieval algorithms and improving the applicability of remote sensing precipitation products.…”
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Overcoming therapeutic resistance in driver-negative NSCLC: Immunomodulatory mechanisms and clinical efficacy of Camrelizumab-chemotherapy combination in a real-world cohort by Yan Ge, Yang Zhao

“…This real-world evidence supports further investigation into resistance biomarkers and adaptive treatment algorithms to optimize immunotherapy integration in resistant NSCLC. …”
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Sodium Propionate Alleviates Atopic Dermatitis by Inhibiting Ferroptosis via Activation of LTBP2/FABP4 Signaling Pathway by Xie A, Li W, Ye D, Yin Y, Wang R, Wang M, Yu R

“…Analysis using three algorithms identified potential therapeutic targets of SP. …”
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Evaluation of Real-World Evidence to Assess Effectiveness Outcomes of Janus Kinase Inhibitors for Rheumatoid Arthritis: A Systematic Review of US Studies by Gandy C, Bazzazzadehgan S, Bruera S, Huang Y

“…Six studies applied effectiveness algorithms, with 14.8– 26% of patients meeting effective treatment criteria. …”
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Enhanced Magnetic Resonance Imaging-Based Brain Tumor Classification with a Hybrid Swin Transformer and ResNet50V2 Model by Abeer Fayez Al Bataineh, Khalid M. O. Nahar, Hayel Khafajeh, Ghassan Samara, Raed Alazaidah, Ahmad Nasayreh, Ayah Bashkami, Hasan Gharaibeh, Waed Dawaghreh

“…The suggested model achieves an impressive accuracy of 99.9% on the binary-labeled dataset and 96.8% on the four-labeled dataset, outperforming the VGG16, MobileNetV2, Resnet50V2, EfficientNetV2B3, ConvNeXtTiny, and convolutional neural network (CNN) algorithms used for comparison. This demonstrates that the Swin transducer, when combined with Resnet50V2, is capable of accurately diagnosing brain tumors. …”
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Unraveling shared diagnostic genes and cellular microenvironmental changes in endometriosis and recurrent implantation failure through multi-omics analysis by Dongxu Qin, Yongquan Zheng, Libo Wang, Zhenyi Lin, Yao Yao, Weidong Fei, Caihong Zheng

“…Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to identify key genes. Machine learning algorithms, including Random Forest (RF) and XGBoost, were utilized to screen for shared diagnostic genes, which were subsequently validated through receiver operating characteristic (ROC) analysis and clinical prediction models. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Additionally, multi-factor logistic regression analysis identified clinical predictors associated with PD-RBD, and these clinical features were integrated with the radiomics signatures to develop predictive models using various machine learning algorithms. The model exhibiting the best performance was selected, and receiver operating characteristic (ROC) curves were used to evaluate its performance in both the training and testing sets. …”
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A novel nomogram for survival prediction in renal cell carcinoma patients with brain metastases: an analysis of the SEER database by Fei Wang, Xihao Wang, Zhigang Feng, Jun Li, Hailiang Xu, Hengming Lu, Lianqu Wang, Zhihui Li

“…Potential risk factors were initially screened applying the eXtreme Gradient Boosting (XGBoost) and Random Forest (RF) machine learning algorithms. Subsequently, multivariate COX regression analysis was performed to identify independent risk factors for constructing the predictive nomogram. …”
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Using random forests to forecast daily extreme sea level occurrences at the Baltic Coast by K. Bellinghausen, B. Hünicke, E. Zorita

“…The method can, therefore, be used as a pre-warning system to trigger the application of more sophisticated algorithms that estimate the height of the ensuing extreme sea level or as a warning to run larger ensembles with physically based numerical models.…”
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SPYDER: QoS-Aware Radio Resource Allocation in Multiuser ISAC-Capable C-V2X Networks by Syed Najaf Haider Shah, Aamir Ullah Khan, Christian Schneider, Joerg Robert

“…To counteract this, we employ sparse reconstruction algorithms within the compressed sensing framework, enhancing flexibility in TF resource allocation and providing high-resolution radar sensing despite uncoordinated resource selection. …”
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Decoding bacterial methylomes in four public health-relevant microbial species: nanopore sequencing enables reproducible analysis of DNA modifications by Valentina Galeone, Johanna Dabernig-Heinz, Mara Lohde, Christian Brandt, Christian Kohler, Gabriel E. Wagner, Martin Hölzer

“…Recent advancements in real-time Nanopore sequencing and basecalling algorithms have enabled the direct detection of modified bases from raw signal data, eliminating the need for bisulfite treatment of DNA. …”
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Computationally Optimized Hemagglutinin Proteins Adjuvanted with Infectimune^® Generate Broadly Protective Antibody Responses in Mice and Ferrets by James D. Allen, Xiaojian Zhang, Jessica M. Medina, Matthew H. Thomas, Amanda Lynch, Ron Nelson, Julia Aguirre, Ted M. Ross

“…Thanks to advances in viral surveillance and sequencing, influenza vaccine antigens can now be optimized using computationally derived methodologies and algorithms to enhance their immunogenicity. <b>Methods:</b> Mice and ferrets that had been previously exposed to historical H1N1 and H3N2 influenza viruses were vaccinated intramuscularly with bivalent mixtures of H1 and H3 recombinant hemagglutinin (rHA) proteins, which were generated using a computationally optimized broadly reactive antigen (COBRA) design methodology. …”
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ES-UNet: efficient 3D medical image segmentation with enhanced skip connections in 3D UNet by Minyoung Park, Seungtaek Oh, Junyoung Park, Taikyeong Jeong, Sungwook Yu

“…Conclusion ES-UNet integrates architectural and algorithmic improvements to achieve robust 3D medical image segmentation. …”
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Cytomegalovirus Infection in Adolescents of Russian Federation: Results of Cross-Sectional Population Analysis of Seroprevalence by Ekaterina Yu. Dubonosova, Leyla S. Namazova-Baranova, Elena A. Vishneva, Nikolay A. Mayanskiy, Tatiana V. Kulichenko, Margarita A. Soloshenko

“…Clear understanding of epidemiology and determination of focus population groups is crucial for development of measures and algorithms of congenital CMVI prevention.Objective. …”
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Color-Sensitive Sensor Array Combined with Machine Learning for Non-Destructive Detection of AFB₁ in Corn Silage by Daqian Wan, Haiqing Tian, Lina Guo, Kai Zhao, Yang Yu, Xinglu Zheng, Haijun Li, Jianying Sun

“…Key variables were selected using five feature selection algorithms: Competitive Adaptive Reweighted Sampling (CARS), Principal Component Analysis (PCA), Random Forest (RF), Uninformative Variable Elimination (UVE), and eXtreme Gradient Boosting (XGBoost). …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Three (3) classification algorithms including Random Forest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) were trained using the QoS dataset and then evaluated in order to determine the most effective model based on certain evaluation metrics – accuracy, precision, F1-Score and recall. …”
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