Large Language Model–Assisted Risk-of-Bias Assessment in Randomized Controlled Trials Using the Revised Risk-of-Bias Tool: Usability Study by Jiajie Huang, Honghao Lai, Weilong Zhao, Danni Xia, Chunyang Bai, Mingyao Sun, Jianing Liu, Jiayi Liu, Bei Pan, Jinhui Tian, Long Ge

“…The remaining 40 trials established the internal validation standard, while Cochrane Reviews judgments served as external validation. …”
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Evaluasi Algoritma Machine Learning untuk Klasifikasi dan Prediksi Penggunaan Lahan by Fajar Nugraha, Dwi Putro Tejo Baskoro, Suria Darma Tarigan

“…The models were evaluated using overall accuracy and kappa; the highest accuracy in 2002, 2012, and 2022 were kNN (kappa 0.92), SVM (kappa 0.86), and GMM (kappa 0.74), respectively. The SVM algorithm had the highest average kappa for classification at 0.83, while the CA-ANN model showed the highest kappa value for prediction at 0.65. …”
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The engagement of cortical areas preceding exogenous vergence eye movements. by Monika Wojtczak-Kwaśniewska, Anna Przekoracka-Krawczyk, Rob H J Van der Lubbe

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The diagnostic value of two antigenic domains derived from the Trypanosoma cruzi Tc323 protein in chronic Chagas disease: a study in Brazil by Micaela S. Ossowski, Ângelo Antônio Oliveira Silva, Ângelo Antônio Oliveira Silva, Emily Ferreira Santos, Emily Ferreira Santos, Leonardo Maia Leony, Leonardo Maia Leony, Fred Luciano Neves Santos, Fred Luciano Neves Santos, Fred Luciano Neves Santos, Karina A. Gómez

“…Both antigens showed a specificity of 97.9%, while sensitivity was 79.5% for rTcD3 and 81.5% for rTcD6. …”
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Factors associated with tuberculosis drug resistance among presumptive multidrug resistance tuberculosis patients identified in a DRTB surveillance study in western Kenya by Albert Okumu, James Orwa, Ruth Sitati, Isaiah Omondi, Ben Odhiambo, Jeremiah Ogoro, George Oballa, Benjamin Ochieng, Steve Wandiga, Collins Ouma

“…Three hundred and ninety (390) sputum sample isolates from among presumptive multidrug TB patients, were analyzed for TB drug resistance as per Ministry of Health (MoH) TB program diagnostic algorithm. Frequency and percentages were used to summarize categorical data while median and interquartile range (IQR) were used for continuous data. …”
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Online Asynchronous Learning over Streaming Nominal Data by Hongrui Li, Shengda Zhuo, Lin Li, Jiale Chen, Tianbo Wang, Jun Tang, Shaorui Liu, Shuqiang Huang

“…To address these challenges, we propose a novel algorithm, termed <i>Online Asynchronous Learning over Streaming Nominal Data</i> (OALN), which maps heterogeneous data into a continuous latent space and leverages a model pool alongside a hint mechanism to effectively manage asynchronous labels. …”
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Simulating Argo float trajectories and along-track physical and biogeochemical variability in the California Current System by Xiao Liu, Xiao Liu, John P. Dunne, Elizabeth J. Drenkard, Gregory C. Johnson

“…Floats drifting at shallower depths (200 m and 500 m) tend to sample larger variability associated with larger sampled area, while those drifting at 1000 m show the strongest association with eddy-like ocean features. …”
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Optimizing Superior Seed Bunches: A New Approach to Artificial Pollination with Machine Learning Models by Yabani Yabani, Retna Astuti Kuswardani

“…The K-means clustering algorithm is applied to group data based on similarities in key variables. …”
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Monitoring and forecasting of land use/land cover (LULC) in Al-Hassa Oasis, Saudi Arabia based on the integration of the Cellular Automata (CA) and the Cellular Automata-Markov Mod... by Ashraf Abdelkarim

“…The maximum likelihood classifier (MLC) method was used as a supervised classification algorithm to super control classification coefficients. …”
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Chip Design of Multithreaded and Pipelined RISC-V Microcontroller Unit by Mao-Hsu Yen, Yih-Hsia Lin, Tzu-Feng Lin, Yu-Hui Chen, Yuan-Fu Ku, Chien-Ting Kao

“…Based on the executable four-thread architecture, we developed two to four RISC-V architectures with different numbers of ALUs and a dispatch algorithm. This architecture allows for the simultaneous delivery of multiple instructions, enabling parallel processing of instructions and increasing efficiency. …”
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Analysis of the Dynamic Process of Tornado Formation on 28 July 2024 by Xin Zhou, Ling Yang, Shuqing Ma, Ruifeng Wang, Zhaoming Li, Yuchen Song, Yongsheng Gao, Jinyan Xu

“…To explore the dynamic and thermodynamic changes during the tornado’s life cycle, high-resolution spatiotemporal data from Foshan’s X-band phased-array radar and the direct wind field synthesis algorithm were used to reconstruct the 3D wind field. …”
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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…In this paper, we propose the OnLine Variational Gaussian Process (OLVGP) algorithm, which introduces a novel approach for dynamically managing the number of inducing points based on the concept of eigenfunction inducing features. …”
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Multimodal AI diagnostic system for neuromyelitis optica based on ultrawide-field fundus photography by Simin Gu, Tiancheng Bao, Tao Wang, Qiting Yuan, Weiguang Yu, Jiayi Lin, Haocheng Zhu, Shihai Cui, Yi Sun, Xiuhua Jia, Lina Huang, Shiqi Ling

“…PurposeWhile deep learning (DL) has demonstrated significant utility in ocular diseases, no clinically validated algorithm currently exists for diagnosing neuromyelitis optica (NMO). …”
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Image Visual Quality: Sharpness Evaluation in the Logarithmic Image Processing Framework by Arnaud Pauwelyn, Maxime Carré, Michel Jourlin, Dominique Ginhac, Fabrice Meriaudeau

“…Such algorithms multiply (×2, ×3, ×4) the resolution of an image using powerful tools (deep learning, neural networks) while correcting the potential defects (blur, noise) that could be generated by the resolution extension itself. …”
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Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…However, DL models often demand substantial computational resources and large datasets, while DT algorithms lack generalizability. To address these limitations, this study proposes a novel parallel boosting neural network (PBNN) framework that integrates boosting algorithms with a feedforward neural network (FFNN). …”
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Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors by Wentong Hu, Donghao Miao, Chi Zhang, Zixian He, Wenquan Gu, Dongguo Shao

“…The best IOA-ML model for total phosphorus (TP), total nitrogen (TN), and permanganate index (CODMn) was extreme gradient boosting optimized by genetic algorithm (GA-XGB), while that for dissolved oxygen (DO) and turbidity was categorical boosting regression optimized by GA (GA-CBR). …”
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Fusion Classification Method Based on Audiovisual Information Processing by Peiju Chen, Xuan Zhang, Huijun Zhao, Huiliang Cao, Xuemei Chen, Xiaochen Liu

“…This paper addresses the inadequacies of single-modal target classification by proposing a target classification algorithm based on audiovisual fusion. The innovative contributions of this work are as follows. (1) To resolve the issue of the lack of correlation between audio signals and image signals, we introduce a method that converts audio signals into spectrograms and fuses them with target images. …”
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A Clinical Case of Two-Stage Visual-Functional Rehabilitation of a Patient with Postinfectious Central Corneal Opacity in Combination with Mixed Astigmatism Using Laser Keratorefra... by N. V. Maychuk, I. A. Mushkova, M. R. Obraztsova

“…To achieve high visual-functional rehabilitation while preserving the native lens, a two-stage treatment algorithm was developed using technologies of laser corneal refractive surgery. …”
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Construction and validation of a readmission risk prediction model for elderly patients with coronary heart disease by Hanyu Luo, Benlong Wang, Rui Cao, Jun Feng

“…The XGBoost model's area under the ROC curve (AUC) reached 0.903, while the external validation dataset yielded an AUC of 0.891, further validating the model's predictive accuracy and its ability to generalize across different datasets.ConclusionTyG-BMI, RDW, and diabetes mellitus at the time of admission are the factors affecting readmission of elderly patients with coronary artery disease, and the model constructed based on the XGBoost algorithm for readmission risk prediction has good predictive efficacy, which can provide guidance for identifying high-risk patients and timely intervention strategies.…”
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Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition by Zeinab Hassani, Davud Mohammadpur, Hossein Safari

“…We investigate the use of long short-term memory (LSTM) and decomposition-LSTM (DLSTM) networks, combined with an ensemble algorithm, to predict solar flare occurrences using time series data from the GOES catalog. …”
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