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  1. 1681

    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

    Published 2025-03-01
    “…Single-cell analysis was conducted to investigate the expression patterns of these diagnostic genes across various cellular subpopulations. …”
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  2. 1682

    Predictive performance of risk prediction models for lung cancer incidence in Western and Asian countries: a systematic review and meta-analysis by Yah Ru Juang, Lina Ang, Wei Jie Seow

    Published 2025-03-01
    “…Our review also highlights a significant gap in prediction models for never-smokers. Future research should focus on externally validating existing Asian models or incorporating relevant Asian risk factors into widely used Western models (PLCOM2012) to better account for unique risk profiles and lung cancer progression patterns in Asian populations.…”
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  3. 1683
  4. 1684

    Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

    Published 2023-01-01
    “…Optimizing AI models in decision-making could mitigate the effects of three research issues: malfunctioning medical devices, high maintenance costs, and the lack of a strategic maintenance framework. …”
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  5. 1685

    Exploring the role of ferroptosis in pemphigus: identification of diagnostic markers and regulatory mechanisms by Jing Mao, Jianping Lan, Zheyu Zhuang, Ying Chen, Ying Chen, Yushan Ou, Xinhong Su, Xueting Zeng, Fuchen Huang, Zequn Tong, Xiaoqing Lv, Xiaoqing Lv, Xiaoqing Lv, Hui Ke, Zhenlan Wu, Ying Zou, Bo Cheng, Bo Cheng, Bo Cheng, Chao Ji, Chao Ji, Chao Ji, Ting Gong

    Published 2025-06-01
    “…This study aims to investigate the expression patterns and potential biological functions of ferroptosis-related genes in pemphigus, as well as their regulatory mechanisms.MethodsTo achieve this, skin samples from five pemphigus patients and five healthy controls were collected from Fujian Medical University Union Hospital. …”
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  6. 1686

    Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition by Rafael T. Sousa, Gustavo D. M. Silva, Paula L. L. Pinto, Juliano Backes, Amanda S. Mota, Thiago M. Paixao, Maria G. S. Teixeira, Wilian H. Hisatugu, Anilton S. Garcia, Kelly S. Prado, Rodrigo S. Dias, Marco A. Galletta, Hermano Tavares

    Published 2025-01-01
    “…By leveraging machine learning techniques to analyze speech patterns, this research seeks to offer a non-invasive, objective, and accessible method for early detection and intervention. …”
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  7. 1687

    The Convergence of AI and animal-inspired robots for ecological conservation by Naqash Afzal, Mobeen ur Rehman, Lakmal Seneviratne, Irfan Hussain

    Published 2025-03-01
    “…By harnessing the capabilities of AI-driven animal robots, researchers can gain a multifaceted toolkit to explore and understand the behaviors, communication patterns, and ecological roles of various species. …”
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  8. 1688

    A novel ensemble model for fall detection: leveraging CNN and BiLSTM with channel and temporal attention by Sarita Sahni, Sweta Jain, Sri Khetwat Saritha

    Published 2025-04-01
    “…To address this issue, researchers propose integrating attention mechanisms, which help prioritize important information from the sensors and reduce the impact of over lapping activity patterns. …”
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  9. 1689

    Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

    Published 2024-11-01
    “…It offers sophisticated algorithms that can identify and discover hidden patterns and provide insights into complex biological networks. …”
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  10. 1690

    Estimation and evaluation of iron reserves in the eastern area of Eileh1 mine, Razavi Khorasan province by Hamid Esmati Daroneh, Maryam Gholamzadeh

    Published 2024-12-01
    “…The software utilized in this research includes Rockworks and Surpac, both of which are comprehensive and powerful tools for imaging, modeling, and analyzing geological information and exploratory data, as well as for performing various modeling tasks based on the type and amount of data available. …”
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  11. 1691

    QuantiFly: Robust Trainable Software for Automated Drosophila Egg Counting. by Dominic Waithe, Peter Rennert, Gabriel Brostow, Matthew D W Piper

    Published 2015-01-01
    “…The basis of the QuantiFly software is an algorithm which applies and improves upon an existing advanced pattern recognition and machine-learning routine. …”
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  12. 1692

    Exploration of Epigenetic Mechanisms and Biomarkers Among Patients with Very-Late-Onset Schizophrenia-Like Psychosis by Gan Y, Yue W, Sun J, Yang D, Fang C, Zhou Z, Yin J, Zhou H

    Published 2025-04-01
    “…Yansha Gan,1,* Weihua Yue,2,* JiaoJiao Sun,1 DanTing Yang,1 ChunXia Fang,1 Zhenhe Zhou,1 JiaJun Yin,1 Hongliang Zhou3 1The Affiliated Mental Health Center of Jiangnan University, Wuxi, Jiangsu, 214151, People’s Republic of China; 2National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, 100191, People’s Republic of China; 3Department of Psychology, The Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu, 214100, People’s Republic of China*These authors contributed equally to this workCorrespondence: JiaJun Yin, The Affiliated Mental Health Center of Jiangnan University, Wuxi, Jiangsu, 214151, People’s Republic of China, Email yinjiajun@jiangnan.edu.cn Hongliang Zhou, Department of Psychology, The Affiliated Hospital of Jiangnan University, No. 200, Huihe Road, Binhu District, Wuxi City, Jiangsu Province, People’s Republic of China, Email Hongliangzh2022@hotmail.comObjective: This study aimed to identify DNA methylation patterns associated with Very Late-Onset Schizophrenia-like Psychosis (VLOSLP) and to develop methylation-based biomarkers that differentiate VLOSLP from Schizophrenia (SCZ) and Alzheimer’s Disease (AD).Methods: We analyzed methylation microarray datasets (n = 1218) from SCZ and AD patients obtained from the GEO database. …”
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  13. 1693
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  15. 1695

    Machine learning applied to the design and optimization of polymeric materials: A review by Sudarsan M. Pai, Karim A. Shah, Sruthi Sunder, Rodrigo Q. Albuquerque, Christian Brütting, Holger Ruckdäschel

    Published 2025-04-01
    “…Machine learning (ML) offers a promising solution to this issue. By leveraging ML algorithms, researchers can accelerate the design process, predict material properties more rapidly, and optimize formulations. …”
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  16. 1696
  17. 1697

    Network capacity with probit-based stochastic user equilibrium problem. by Lili Lu, Jian Wang, Pengjun Zheng, Wei Wang

    Published 2017-01-01
    “…Among different stochastic user equilibrium (SUE) traffic assignment models, the Logit-based stochastic user equilibrium (SUE) is extensively investigated by researchers. It is constantly formulated as the low-level problem to describe the drivers' route choice behavior in bi-level problems such as network design, toll optimization et al. …”
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  18. 1698

    Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

    Published 2025-12-01
    “…We establish soil sampling sites in this region, employ Google Earth Engine algorithms to develop models for soil salinity inversion and land use classification, and analyze the change patterns of land salinization and land use types. …”
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  19. 1699
  20. 1700

    ANALISIS PROSES BERPIKIR KOMPUTASI SISWA PADA MATERI BARISAN ARITMETIKA BERDASARKAN KECERDASAN MAJEMUK by Rosevita Melati, Toto Nusantara, Mochammad Hafiizh

    Published 2024-12-01
    “…Visual-spatial intelligence students excelled at pattern detection throughout the algorithmic thinking level. …”
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