Estimation of common breaks in linear panel data models via screening and ranking algorithm by Fuxiao Li, Yanting Xiao, Zhanshou Chen

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Screening of glioma susceptibility SNPs and construction of risk models based on machine learning algorithms by Mingjun Hu, Jie Hao, Jie Wei

“…This study aimed to develop a predictive model for glioma risk by these screened key SNPs in the Chinese Han population. …”
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Development of a cataract screening model using an open dataset and deep machine learning algorithms by S.N. Sakhnov, K.D. Axenov, L.E. Axenova, V.V. Vronskaya, A.O. Martsinkevich, V.V. Myasnikova

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Comparison of Machine Learning Algorithms to Predict Down Syndrome During the Screening of the First Trimester of Pregnancy by Eduardo Alonso, Andoni Beristain, Jorge Burgos, Ibai Gurrutxaga

“…Various machine learning models, including statistical, linear, and ensemble models, were trained using a pseudo-anonymized dataset of 90,532 screening patients. …”
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MODEL OF ORGANIZATION OF KIDNEY CANCER EARLY DIAGNOSIS by V. G. Moreva, G. N. Alekseeva, P. F. Kiku, L. I. Gurina, K. M. Sabirova, V. N. Rasskazova

“…The model included a population questionnaire to identify risk factors and algorithm of patient routing («roadmap») with suspected kidney cancer for in-depth examination and treatment. …”
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Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms by Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, Ana Sanches Silva, Carla Brites

“…Similarly, ANN models showed good predictive performance, particularly for FB1 + FB2, with R = 0.99, and the root means square error (RMSE) of 131 μg/kg for calibration; and R = 0.95, RMSE = 656 μg/kg for validation.These findings underscore the efficacy of NIR spectroscopy as a rapid, non-destructive tool for fumonisin screening in maize, with chemometric algorithms enhancing model accuracy, offering a valuable method for ensuring food safety.…”
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Refining the Feasibility of Machine‐Learning‐Based Diagnostic Model Utilizing Gut Microbiota Analysis for Colorectal Cancer Screening by Shintaro Okumura, Yusuke Konishi, Taku Kitano, Tomonori Matsumoto, Kazutaka Obama, Satoshi Nagayama, Eiji Hara

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Establishment and assessment of an early screening model for cervical cancer based on single-cell Raman spectroscopy combined with machine learning algorithms by MA Dongmei, ZHAO Wenjie, LIU Shihai, XU Haicang, CAI Duo, JI Yuetong, XU Jian, GUO Cancan, MA Bo, PAN Huazheng

“…Objective To establish an early screening model for cervical cancer based on single-cell Raman spectroscopy (SCRS) combined with machine learning algorithms, and to assess the performance of the model. …”
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APPLICATION OF THE ENTROPY-PROBABILISTIC MODEL OF THE X-RAY TELEVISION INTROSCOPE OPERATOR IN THE ALGORITHM OF THE COMPUTER SIMULATOR DURING TRAINING OF SECURITY SCREENING POINT EMPLOYEES by A. K. Volkov, V. V. Iudaev, A. V. Dormidontov

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The utility of an artificial intelligence model based on decision tree and evolution algorithm to evaluate steatotic liver disease in a primary care setting by A.C. Goulart, A.P. Alencar, G. Tunes, L.L.T. Bianchi, M.H. Miname, C.M. Padilha, J.M.S. Pescuma, A.L.C.C. Rodrigues, B.B. Henares, M.S. de Almeida, T.A.O. Machado, D.H. Syllos, Y.P. Wang, M. Rienzo

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Research and application of optimization of physical education training model based on multi-objective differential evolutionary algorithm by Man Wu

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Multi-Objective Parameter Optimization of Rotary Screen Coating Process for Structural Plates in Spacecraft by Yanhui Guo, Yanpeng Chen, Peibo Li, Xinfu Chi, Yize Sun

Subjects: “…multi-objective optimization algorithm…”
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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…In terms of the robustness of the algorithm and the overall performance comparison of different methods,the proposed algorithm can extract the formant robustly from order 9 to 22, and the model algorithm shows the optimal performance when the formant is extracted from order 18. …”
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Defects Detection in Screen-Printed Circuits Based on an Enhanced YOLOv8n Algorithm by Xinyu Zhang, Jia Wang, Dan Jiang, Yang Li, Xuewei Wang, Han Zhang

“…To address these challenges, a self-made SPC defect data set and an enhanced CAAB-YOLOv8n detection algorithm were developed. A CAD module was integrated into the backbone network to improve the model’s ability to detect bar-shaped features. …”
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Rapid diagnostic algorithms as a screening tool for tuberculosis: an assessor blinded cross-sectional study. by Franz Ratzinger, Harald Bruckschwaiger, Martin Wischenbart, Bernhard Parschalk, Delmiro Fernandez-Reyes, Heimo Lagler, Alexandra Indra, Wolfgang Graninger, Stefan Winkler, Sanjeev Krishna, Michael Ramharter

“…A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms.…”
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A novel machine-learning algorithm to screen for trisomy 21 in first-trimester singleton pregnancies by James Osborne, Chris Cockcroft, Carolyn Williams

“…This study investigates the use of machine-learning algorithms in the prediction of T21 in first-trimester singleton pregnancies and compares their performance to existing screening models.Methods A total of 86,354 anonymised, first trimester, singleton pregnancy screening cases, including 211 with T21, were used to train and test machine-learning models using adaptive boosting technology. …”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…Emerging tools, such as risk prediction models, radiomics, artificial intelligence (AI), and liquid biopsies, enhance the accuracy of screening, allowing for the identification of high-risk individuals who may not meet conventional criteria. …”
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Breast Cancer Screening Using a Modified Inertial Projective Algorithms for Split Feasibility Problems by Pennipat Nabheerong, Warissara Kiththiworaphongkich, Watcharaporn Cholamjiak

“…To detect breast cancer in mammography screening practice, we modify the inertial relaxed CQ algorithm with Mann’s iteration for solving split feasibility problems in real Hilbert spaces to apply in an extreme learning machine as an optimizer. …”
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Hybrid convolutional neural network optimized with an artificial algae algorithm for glaucoma screening using fundus images by M. Shanmuga Eswari, S. Balamurali, Lakshmana Kumar Ramasamy

“…Objective We developed an optimized decision support system for retinal fundus image-based glaucoma screening. Methods We combined computer vision algorithms with a convolutional network for fundus images and applied a faster region-based convolutional neural network (FRCNN) and artificial algae algorithm with support vector machine (AAASVM) classifiers. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. …”
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