Development and validation of a 3-D deep learning system for diabetic macular oedema classification on optical coherence tomography images by Mingzhi Zhang, Tsz Kin Ng, Yi Zheng, Guihua Zhang, Jian-Wei Lin, Ji Wang, Jie Ji, Peiwen Xie, Yongqun Xiong, Hanfu Wu, Cui Liu, Huishan Zhu, Jinqu Huang, Leixian Lin

“…The deep learning (DL) performance was compared with the diabetic retinopathy experts.Setting Data were collected from Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Chaozhou People’s Hospital and The Second Affiliated Hospital of Shantou University Medical College from January 2010 to December 2023.Participants 7790 volumes of 7146 eyes from 4254 patients were annotated, of which 6281 images were used as the development set and 1509 images were used as the external validation set, split based on the centres.Main outcomes Accuracy, F1-score, sensitivity, specificity, area under receiver operating characteristic curve (AUROC) and Cohen’s kappa were calculated to evaluate the performance of the DL algorithm.Results In classifying DME with non-DME, our model achieved an AUROCs of 0.990 (95% CI 0.983 to 0.996) and 0.916 (95% CI 0.902 to 0.930) for hold-out testing dataset and external validation dataset, respectively. …”
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Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…A machine learning study developed a parallel Convolutional Neural Network algorithm with 96.4% recall and 99.1% precision for study screening. …”
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Exploring the role of repetitive negative thinking in the transdiagnostic context of depression and anxiety in children by Kuiliang Li, Lei Ren, Xiao Li, Chang Liu, Xuejiao Tan, Ming Ji, Xi Luo

“…Network analysis revealed that RNT’s core features exhibited the highest bridge betweenness and bridge expected influence, indicating a critical mediating role in the co-occurrence of symptoms. The random forest model showed optimal predictive performance (AUC = 0.90, recall = 0.95), supporting its applicability for early screening. …”
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MYOPIA PREVALENCE AMONG STUDENTS DURING COVID-19 PANDEMIC. A SYSTEMATIC REVIEW AND META-ANALYSIS by Natasha Hana Savitri, Adinda Sandya Poernomo, Muhammad Bagus Fidiandra1, Eka Candra Setyawan1, Arinda Putri Auna Vanadia1, Bulqis Inas Sakinah1, Lilik Djuari

“…Data retrieval used the PICO method and journal adjustments were selected using the PRISMA algorithm. Data analysis was performed using a random-effects model. …”
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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

“…The model's performance was evaluated in a cloud-based environment using two datasets: ORIGA and G1020. …”
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Design and predict the potential of imidazole-based organic dyes in dye-sensitized solar cells using fingerprint machine learning and supported by a web application by Mohamed M. Elsenety

“…Among of these, Deep Neural Network models of MLPRegressor algorithm based on the daylight fingerprint shows a significant coefficient of determination combined with the lowest errors. …”
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3D Film Animation Image Acquisition and Feature Processing Based on the Latest Virtual Reconstruction Technology by Siwei Wu, Shan Xiao, Yihua Di, Cheng Di

“…Finally, the target 3D face is reconstructed using the feature points of the target face for model matching. The experimental results show that the algorithm reconstructs faces with high realism and accuracy, and the algorithm can reconstruct expression faces.…”
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Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network by Aythem Khairi Kareem, Mohammed M. AL-Ani, Ahmed Adil Nafea

“…Results strongly suggest that 1D CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorder …”
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Evaluating the role of insulin resistance in chronic intestinal health issues: NHANES study findings by Dongyao Zhao, Meihua Zhao, Bing Gao, He Lu

“…Key variables were selected via the Boruta algorithm and incorporated into weighted multivariate logistic regression models. …”
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LABORATORY OF CLINICAL IMMUNOLOGY N.V. SKLIFOSOVSKY RESEARCH INSTITUTE FOR EMERGENCY MEDICINE (HISTORY AND PRESENT) by M. A. Godkov, G. V. Bulava

“…During 45 years of work of immunological service formed the algorithm of the adequate immunological screening was formed, number of innovative methods of diagnosis was developed, the ideology of post-test counseling of patients by immunologists was created, mathematical methods of storage, modeling and processing of research results was introduced. …”
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Identification and Evaluation of Lipocalin-2 in Sepsis-Associated Encephalopathy via Machine Learning Approaches by Hu J, Chen Z, Wang J, Xu A, Sun J, Xiao W, Yang M

“…Subsequently, neuroinflammation-related genes were obtained to construct a neuroinflammation-related signature. The AddModuleScore algorithm was used to calculate neuroinflammation scores for each cell subpopulation, whereas the CellCall algorithm was used to assess the crosstalk between neutrophils and other cell subpopulations. …”
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A deep-learning approach to predict reproductive toxicity of chemicals using communicative message passing neural network by Owen He, Daoxing Chen, Yimei Li

“…In independent test sets, ReproTox-CMPNN achieved a mean AUC of 0.946, ACC of 0.857 and F1 score of 0.846, surpassing traditional algorithms to establish itself as a new state-of-the-art model in this field. …”
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Integrated analysis of single-cell RNA-seq and spatial transcriptomics to identify the lactylation-related protein TUBB2A as a potential biomarker for glioblastoma in cancer cells... by Yifan Xu, Chonghui Zhang, Jinpeng Wu, Pin Guo, Nan Jiang, Chao Wang, Yugong Feng

“…Notably, the expression levels of these three hub genes and the lactylation level of TUBB2A in GBM tissues were significantly higher compared to those in normal tissues.ConclusionsWe propose and validate a IQR lactylation screening method that provides potential insights for GBM therapy and an effective framework for developing gene screening models applicable to other diseases and pathogenic mechanisms.…”
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Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization by Riyadh M. Alzahrani, Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmed Farag Salem Babetat, Maryam Alhashim, Abdulrahman Alduraywish, N. B. Prakash, Eddie Y. K. Ng

“…An Enhanced Particle Swarm Optimization (EPSO) algorithm is integrated to automatically fine-tune CNN hyperparameters, thereby minimizing manual effort and enhancing computational efficiency. …”
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Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

“…Advanced machine learning (ML) and deep learning (DL) methods have recently been utilized in Drug Response Prediction (DRP), and these models use the details from genomic profiles, such as extensive drug screening data and cell line data, to predict the response of drugs. …”
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Neurological post-COVID syndrome is associated with substantial impairment of verbal short-term and working memory by Jeyanthan Charles James, Hannah Schulze, Nadine Siems, Christian Prehn, Daniel R. Quast, Nadine Trampe, Ralf Gold, Simon Faissner

“…Neurologic PCS patients had more complaints with significantly higher fatigue scores as well as higher levels of depressive and anxiety symptoms compared to Non-PCS and HC. …”
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LncRNAs regulates cell death in osteosarcoma by Ping’an Zou, Zhiwei Tao, Zhengxu Yang, Tao Xiong, Zhi Deng, Qincan Chen, Li Niu

“…Three machine learning algorithms—Support Vector Machine, Random Forest, and Generalized Linear Model—were utilized to select feature genes. …”
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How math shapes the world of life science animation by Rafael Oliveira, Evellyn Araujo Dias, Evellyn Araujo Dias, Ricardo Santos, Ricardo Santos, Vinicius Cotta-De-Almeida, José Aguiar Coelho Nt, José Aguiar Coelho Nt, José Aguiar Coelho Nt, Luiz Anastácio Alves

“…This paper elucidates the role of matrix manipulation in animating figures on screens, elucidates the distinctions between Scalable Vector Graphics (SVG), bitmap and raster images, and unveils the inner workings of the Bresenham algorithm in the context of rendering lines on screens. …”
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Technical Code Analysis of Geomagnetic Flaw Detection of Suppression Rigging Defect Signal Based on Convolutional Neural Network by Gang Zhao, Changyu Han, Zhongxiang Yu, Zhipan Li, Guoao Yu, Hongmei Zhang, Dadong Zhao, Zhengyi Jiang

“…The single-stage object detection algorithm YOLOv5 (You Only Look Once) based on convolutional neural network model calculation is used, the scale detection layer and positioning loss function of the YOLOv5 algorithm are improved and optimized, and the improved YOLOv5 algorithm is used for experiments. …”
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Neutrophil extracellular traps-related genes contribute to sepsis-associated acute kidney injury by Tang Shaoqun, Yu Xi, Wang Wei, Luo Yaru, Lei Shaoqing, Qiu Zhen, Yang Yanlin, Sun Qian, Xia Zhongyuan

“…Differentially expressed genes were screened by “limma” package in R. Least absolute shrinkage and selection operator algorithm was applied to identify the hub genes. …”
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