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  1. 121

    Algorithmic indexing in MEDLINE frequently overlooks important concepts and may compromise literature search results by Alexandre Amar-Zifkin, Taline Ekmekjian, Virginie Paquet, Tara Landry

    Published 2025-01-01
    “…Three main issues with algorithmically-indexed records were identified: 1) inappropriate MeSH assigned due to acronyms, evocative language, exclusions of populations, or related records; 2) concepts represented by more general MeSH while a more precise MeSH is available; and 3) a significant concept not represented in the indexing at all. …”
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  2. 122

    Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification by Zne-Jung Lee, Jing-Xun Cai, Liang-Hung Wang, Ming-Ren Yang

    Published 2024-12-01
    “…<b>Results:</b> The target genes were screened and combined with data augmentation and ensemble boosting algorithms. …”
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  3. 123

    Developing an Algorithm for Detecting Suspicious Trades in Tehran Stock Exchange Based on Spoof Trading Model by Reza Tehrani, Saeed Fallahpour, Hamid Nouralidokht

    Published 2023-03-01
    “…More specifically, this paper studies manipulated stocks by looking at market microstructure (intraday transactions) and aims to introduce an algorithm for detecting suspicious trades so that regulators can detect them beforehand. …”
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  4. 124

    Improved adaptive FPGA dark channel prior dehazing algorithm for edge applications in agricultural scenarios by Qunpeng Gao, Baiquan Qian, Fengqi Yu, Liye Chen, Peng Gao, Jiatao Wu, Zonghong Li, Weixing Wang, C.V. Jiaxing Xie

    Published 2025-12-01
    “…Through field data acquisition and a self-developed adaptive mechanism, the system achieves adaptive processing across varying fog densities while mitigating the screen flickering inherent to adaptive systems. Based on the sky brightness distribution, a more effective sky-region segmentation strategy was designed to address overexposure in the sky region of dehazed images. …”
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  5. 125

    A Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing by Jiayuan Shen, Bing Han, Yang Li, Zongxu Pan, Di Yin, Yugang Feng, Guangzuo Li

    Published 2024-11-01
    “…We take the data of Sentinel-1 terrain observation with progressive scan (TOPS) mode as an example. By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. …”
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  6. 126
  7. 127

    Data transmission algorithm for mobile wireless sensor network based on power loss equalization control mechanism by Lijun LI, Fuquan ZHANG, Hongfei LIU

    Published 2018-11-01
    “…In order to solve the problem of synchronization addressing and the inadequacy of power interaction among nodes in the current mobile wireless sensor network,a new data transmission algorithm for mobile wireless sensor network was proposed.Firstly,the broadcast mechanism was adopted to realize synchronous control packet transmission and reduce the pressure caused by the synchronization flow to the addressing process.Then regional node flow valve control mechanism was used,and data traffic between sink nodes and regional node links were recorded and got by interception,flow link equalization was further adopted to promote traffic equalization.in the further step.Finally,the limited bandwidth based on wheel number-sink link jitter screening mode could be identified,and the transmission failure due to limited bandwidth was reduced.Simulation results show that compared with the bandwidth of the root zone node and widely used in limiting transmission algorithm,node link stability encoding algorithm and hierarchical encoding algorithm,the data transmission bandwidth can be improved,the packet loss rate can be reduced,and the practical needs can be better met.…”
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  8. 128

    Aggregation of cardiovascular risk factors in a cohort of 40-year-olds participating in a population-based health screening program in Sweden by Beata Borgström Bolmsjö, Emelie Stenman, Anton Grundberg, Kristina Sundquist

    Published 2024-11-01
    “…SCORE2 was calculated according to the algorithm provided by the SCORE2 working group and ESC (European Society of Cardiology) Cardiovascular Risk Collaboration. …”
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  9. 129

    An Integrated Fault Diagnosis Method for Rotating Machinery Based on Improved Multivariate Multiscale Amplitude-Aware Permutation Entropy and Uniform Phase Empirical Mode Decomposi... by Jiancheng Gong, Xiaoqiang Yang, Fan Pan, Wuqiang Liu, Fuming Zhou

    Published 2021-01-01
    “…This algorithm is combined with the Uniform Phase Empirical Mode Decomposition (UPEMD) method and the t-distributed Stochastic Neighbor Embedding (t-SNE) method, forming a new time-frequency multiscale feature extraction method. …”
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  10. 130

    Multimodal Approach (MRI and Ultrasonography) to the Diagnosis of Fetal Congenital Heart Diseases by A. V. Pomortsev, M. N. Karakhalis, N. V. Krivonosova, K. F. Goloseev

    Published 2024-11-01
    “…In 85.7% of the fetuses, the findings of different imaging techniques fully coincided with the autopsy findings.Conclusions: In this cohort of pregnant women, the second screening should include more examinations to verify the diagnosis of CHD. …”
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  11. 131

    Identification and Validation of NK Marker Genes in Ovarian Cancer by scRNA-seq Combined with WGCNA Algorithm by Xin He, Weiwei Feng

    Published 2023-01-01
    “…The WGCNA algorithm screens NK cell marker genes based on bulk RNA transcriptome patterns. …”
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  12. 132

    MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. by Chao Wang, Quan Zou

    Published 2024-11-01
    “…The comparison results shown that MFPSP achieves a more advanced and balanced performance to several state-of-the-art available toolkits. …”
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  13. 133

    Precision Measurement and Feature Selection in Medical Diagnostics using Hybrid Genetic Algorithm and Support Vector Machine by Gowri Subadra K, Sathish Babu P

    Published 2025-07-01
    “…This study contributes to the development of more accurate and efficient breast cancer screening tools to help healthcare providers make informed diagnostic decisions.…”
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  14. 134
  15. 135

    A recurrent neural network and parallel hidden Markov model algorithm to segment and detect heart murmurs in phonocardiograms. by Andrew McDonald, Mark J F Gales, Anurag Agarwal

    Published 2024-11-01
    “…These properties make the algorithm a promising tool for screening of abnormal heart murmurs.…”
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  16. 136

    Feature Selection based on Genetic Algorithm for Classification of Mammogram Using K-means, k-NN and Euclidean Distance by Kameran Adil Ibrahim

    Published 2023-02-01
    “…., the classifications was done on the bases of the features selected using genetic algorithm. Attempts have also been made to study the performance of each feature selected by Genetic Algorithm (GA) in classification. …”
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  17. 137

    Chemoreactome screening of aquacobalamin and heptamethyl ester of cyanoaquacobyrinic acid cytotoxic effects on tumor cells with experimental confirmation on BT-474 and A549 cell by I. Yu. Torshin, M. V. Filimonova, O. A. Gromova, L. A. Maiorova, M. A. Sorokina, D. E. Frolova, A. N. Gromov, I. A. Reyer

    Published 2024-05-01
    “…Experimental studies of tumor cell cultures were carried out using the MTT testwith aquacobalamin and HECСA on cell lines of immortalized (telomerized) fibroblasts (Fb-hTERT), lung carcinoma (A549), and breast duct cancer (BT-474).Results. Chemoreactome screening of the effects of molecules on tumor cells made it possible to obtain estimates of cell growth IC50 for 470 tumor cell lines. …”
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  18. 138

    Predicting Early-Onset Colorectal Cancer in Individuals Below Screening Age Using Machine Learning and Real-World Data: Case Control Study by Chengkun Sun, Erin Mobley, Michael Quillen, Max Parker, Meghan Daly, Rui Wang, Isabela Visintin, Ziad Awad, Jennifer Fishe, Alexander Parker, Thomas George, Jiang Bian, Jie Xu

    Published 2025-06-01
    “…Accurate early prediction and a thorough understanding of the risk factors for early-onset colorectal cancer (EOCRC) are vital for effective prevention and treatment, particularly for patients below the recommended screening age. ObjectiveOur study aims to predict EOCRC using machine learning (ML) and structured electronic health record data for individuals under the screening age of 45 years, with the aim of exploring potential risk and protective factors that could support early diagnosis. …”
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