Screening for More than 1,000 Pesticides and Environmental Contaminants in Cannabis by GC/Q-TOF by Philip L. Wylie, Jessica Westland, Mei Wang, Mohamed M. Radwan, Chandrani G. Majumdar, Mahmoud A. ElSohly

“… A method has been developed to screen cannabis extracts for more than 1,000 pesticides and environmental pollutants using a gas chromatograph coupled to a high-resolution accurate mass quadrupole time-of-flight mass spectrometer (GC/Q-TOF). …”
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Estimated inpatient malnutrition prevalence, screening tool utilization, and dietitian referral rates across hospitals during extension of phase 2 of More-2-Eat by Yingying Xu, Rachel A. Warren, Shirley M. Peters, Sonya Boudreau, Tina N. Strickland, Mari Somerville, Brenda L. MacDonald, Heather Keller, Leah E. Cahill

“…The Integrated Nutrition Pathway for Acute Care (INPAC) is a validated multi-step algorithm that includes screening using the Canadian Nutrition Screening Tool (CNST) and diagnosis using Subjective Global Assessment (SGA). …”
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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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Glitch(ing)! A refusal and gateway to more caring techno-urban worlds? by Mirjana Mitrović, Maja-Lee Voigt

“…With code connecting to concrete in ‘smart’ cities, oppressive, patriarchal, and binary architectures of the urban have been translated into their algorithmic counterparts, too. This particularly excludes people who do not conform to these inscribed norms. …”
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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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Experimental investigations and field applications of a tension estimation method for two linked suspenders using only local vibration measurements by Wen-Hwa Wu, Chien-Chou Chen, Meng-Xuan Wu, Gwolong Lai

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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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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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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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Artificial Intelligence Algorithm to Screen for Diabetic Neuropathy: A Pilot Study by Giovanni Sartore, Eugenio Ragazzi, Francesco Pegoraro, Mario German Pagno, Annunziata Lapolla, Francesco Piarulli

“…<b>Conclusions</b>: The use of an optimized AI algorithm can help estimate the risk of developing DPN, thereby guiding more targeted and in-depth screening, including instrumental assessment using the biothesiometer method.…”
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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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Trisomy 21 screening with αlpha software and the Fetal Medicine Foundation algorithm by L Pistorius, C A Cluver, I Bhorat, L Geerts

“…Different algorithms are used to screen for trisomy 21 in South Africa (SA). …”
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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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Discovery, Biological Evaluation and Binding Mode Investigation of Novel Butyrylcholinesterase Inhibitors Through Hybrid Virtual Screening by Lizi Li, Puchen Zhao, Can Yang, Qin Yin, Na Wang, Yan Liu, Yanfang Li

“…This study employed a quantitative structure–activity relationship (QSAR) model based on ECFP4 molecular fingerprints with several machine learning algorithms (XGBoost, RF, SVM, KNN), among which the XGBoost model showed the best performance (AUC = 0.9740). …”
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