Performance of machine learning-based models to screen obstructive sleep apnea in pregnancy by Jingyu Wang, Wenhan Xiao, Haoyang Hong, Chi Zhang, Min Yu, Liyue Xu, Jun Wei, Jingjing Yang, Yanan Liu, Huijie Yi, Linyan Zhang, Rui Bai, Bing Zhou, Long Zhao, Xueli Zhang, Xiaozhi Wang, Xiaosong Dong, Guoli Liu, Shenda Hong

“…Abstract The purpose of this study is to improve the performance of existing OSA screening tools for pregnant women with machine learning algorithms. …”
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Performance and limitation of machine learning algorithms for diabetic retinopathy screening and its application in health management: a meta-analysis by Mehrsa Moannaei, Faezeh Jadidian, Tahereh Doustmohammadi, Amir Mohammad Kiapasha, Romina Bayani, Mohammadreza Rahmani, Mohammad Reza Jahanbazy, Fereshteh Sohrabivafa, Mahsa Asadi Anar, Amin Magsudy, Seyyed Kiarash Sadat Rafiei, Yaser khakpour

“…Abstract Background In recent years, artificial intelligence and machine learning algorithms have been used more extensively to diagnose diabetic retinopathy and other diseases. …”
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Accuracy improvement in financial sanction screening: is natural language processing the solution? by Seihee Kim, ShengYun Yang

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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

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To Determine the Risk-Based Screening Interval for Diabetic Retinopathy: Development and Validation of Risk Algorithm from a Retrospective Cohort Study by Jinxiao Lian, Ching So, Sarah Morag McGhee, Thuan-quoc Thach, Cindy Lo Kuen Lam, Colman Siu Cheung Fung, Alfred Siu Kei Kwong, Jonathan Cheuk Hung Chan

“…Methods The retrospective cohort data from 117,418 subjects who received systematic DR screening in Hong Kong between 2010 and 2016 were included to develop and validate the risk algorithm using a parametric survival model. …”
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Exploratory Study on Screening Chronic Renal Failure Based on Fourier Transform Infrared Spectroscopy and a Support Vector Machine Algorithm by Yushuai Yuan, Li Yang, Rui Gao, Cheng Chen, Min Li, Jun Tang, Xiaoyi Lv, Ziwei Yan

“…The samples were input into the SVM after division by the Kennard–Stone (KS) algorithm. Compared with other models, the SVM optimized by a grid search (GS) algorithm performed the best. …”
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Empowering Portable Age-Related Macular Degeneration Screening: Evaluation of a Deep Learning Algorithm for a Smartphone Fundus Camera by Ashish Sharma, Taraprasad Das, Bryan Ong, Florian Mickael Savoy, Divya Parthasarathy Rao, Jun Kai Toh, Anand Sivaraman

“…The model was designed to indicate the presence of referable AMD (intermediate and advanced AMD). …”
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High-content chemical and RNAi screens for suppressors of neurotoxicity in a Huntington's disease model. by Joost Schulte, Katharine J Sepp, Chaohong Wu, Pengyu Hong, J Troy Littleton

“…By tracking the subcellular distribution of mRFP-tagged pathogenic Huntingtin and assaying neurite branch morphology via live-imaging, we identified suppressors that could reduce Huntingtin aggregation and/or prevent the formation of dystrophic neurites. The custom algorithms we used to quantify neurite morphologies in complex cultures provide a useful tool for future high-content screening approaches focused on neurodegenerative disease models. …”
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Development and validation of machine learning models for MASLD: based on multiple potential screening indicators by Hao Chen, Jingjing Zhang, Xueqin Chen, Ling Luo, Wenjiao Dong, Yongjie Wang, Jiyu Zhou, Canjin Chen, Wenhao Wang, Wenbin Zhang, Zhiyi Zhang, Yongguang Cai, Danli Kong, Yuanlin Ding

“…This study aimed to utilize multifaceted indicators to construct MASLD risk prediction machine learning models and explore the core factors within these models.MethodsMASLD risk prediction models were constructed based on seven machine learning algorithms using all variables, insulin-related variables, demographic characteristics variables, and other indicators, respectively. …”
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Key gene screening and diagnostic model establishment for acute type a aortic dissection by Yue Pan, Zhiming Yu, Xiaoyu Qian, Xuesong Zhang, Qun Xue, Weizhang Xiao

“…The multi-omics diagnostic model provides a novel tool for early screening, potentially reducing mortality through timely intervention. …”
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Balancing the Parameters of Perforated Solar Screens to Optimize Daylight and Glare Performance in Office Buildings by Aya M.F. El-Bahrawy

“…Perforated solar screens (PSSs) have been widely used as an outer skin for the fully glazed façades of office buildings for their environmental and aesthetic benefits. …”
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Genomic and algorithm-based predictive risk assessment models for benzene exposure by Minyun Jiang, Minyun Jiang, Na Cai, Na Cai, Juan Hu, Lei Han, Lei Han, Fanwei Xu, Baoli Zhu, Baoli Zhu, Baoli Zhu, Baoli Zhu, Boshen Wang

“…AimIn this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.Subject and methodsWe sourced GSE9569 and GSE21862 microarray data from the Gene Expression Omnibus. …”
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Does advancement in marker-less pose-estimation mean more quality research? A systematic review by Shivam Bhola, Shivam Bhola, Hyun-Bin Kim, Hyeon Su Kim, BonSang Gu, Jun-Il Yoo, Jun-Il Yoo

“…Publication frequency trend has accelerated in recent years, with more than half of these studies published after 2021. …”
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METHOD FOR NUMERICAL MODELING OF UNSTEADY SEPARATED FLOW AROUND AIRFOILS MOVING CLOSE TO FLAT SCREEN by T. V. Pogrebnaya, S. D. Shipilov

“…Three different ways of flow modeling (mirror method, fixed or movable screens) were tested. …”
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Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data by Erin B Comartin, Grant Victor, Athena Kheibari, Brian K Ahmedani, Bethany Hedden-Clayton, Richard N Jones, Ted R Miller, Jennifer E Johnson, Lauren M Weinstock, Sheryl Kubiak

“…We hypothesize that a combination of intake screening PAU and the ML model will be the optimal approach, in that the combination will be more accurate and can have practical application in this context. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

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Construction of machine learning-based models for screening the high-risk patients with gastric precancerous lesions by Shuxian Yu, Haiyang Jiang, Jing Xia, Jie Gu, Mengting Chen, Yan Wang, Xiaohong Zhao, Zehua Liao, Puhua Zeng, Tian Xie, Xinbing Sui

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ALGORITHM OF DIAGNOSTICS AND TREATMENT OF AN AGE-RELATED MACULAR DEGENERATION AT PATIENTS WITH CHRONIC PERIPHERAL UVEITIS by Yu. I. Khoroshikh, O. I. Krivosheina, Ye. V. Melekhin

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Research on thyroid nodule segmentation algorithm based on improved U-Net model by Zhou Peng, Wu Zhangjing, Yu Yong, Zhao Yuxuan, Huang Dan, Zhang Min

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A network-based method using a random walk with restart algorithm and screening tests to identify novel genes associated with Menière's disease. by Lin Li, YanShu Wang, Lifeng An, XiangYin Kong, Tao Huang

“…To make the identified genes more reliable, a series of screening tests, including a permutation test, an interaction test and an enrichment test, were designed to select essential genes from those obtained by the RWR algorithm. …”
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