Advancing a machine learning-based decision support tool for pre-hospital assessment of dyspnoea by emergency medical service clinicians: a retrospective observational study by Wivica Kauppi, Henrik Imberg, Johan Herlitz, Oskar Molin, Christer Axelsson, Carl Magnusson

“…The gradient boosting algorithm had the overall best performance, with excellent calibration of the predictions, and consistently showed higher sensitivity to detect SAE than the other methods. …”
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An English Diagnostic Intelligence Evaluation Model Based on Organizational Evolutionary Information Entropy by Haiying Sang

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Symbolic Computation and the Extended Hyperbolic Function Method for Constructing Exact Traveling Solutions of Nonlinear PDEs by Huang Yong, Shang Yadong, Yuan Wenjun

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Improved analysis with spectral-domain optical coherence tomography angiography for evaluating vascular damage in exfoliation syndrome by Rongpei Zhang, Bingying Lin, Hairui Zhang, Yuncheng Ma, Na Xu, Ling Jin, Zhenyu Wang, Lei Tian, Munire Mohetaer, Aizezi Wumaier, Rongxin Chen, Danping Huang

“…The areas under the receiver operating characteristic curve for the SVC FAZ area and OS VD in predicting XFS were both >0.67. Conclusions: The pixel-level FAZ algorithm and VD map derived from OCTA can reflect microvascular damage in XFS. …”
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Clinical significance of a machine learning model based on short-term changes in NT-proBNP after TAVR by Yu Mao, Mengen Zhai, Ping Jin, Gejun Zhang, Haibo Zhang, Lai Wei, Xiaoke Shang, Jian Liu, Yingqiang Guo, Xiangbin Pan, Yang Liu, Jian Yang

“…The 4-year primary end-point rates in the four groups were 13.1 %, 18.0 %, 26.9 %, and 33.3 % (log-rank, p < 0.001). A model for predicting the incidence of the primary end point was based on the random forest algorithm. …”
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Classification and Comparison of Eight Different Growth Curve Methods for Pekin Duck by Hasan Önder, Mine Yılmaz, Mustafa Şahin, Uğur Şen, Sibel Bozkurt, Kadir Erensoy, İsmail Gök, Tolga Tolun, Ahmet Uçar

“…These models can be used for predicting body weight for a specific age from a dimensional perspective. …”
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Constitutive modeling and workability characterization of pre-deformed AZ31 magnesium alloy during hot shear-compression deformation by Junsong Jin, Fangtao Chai, Jinchuan Long, Chang Gao, Shaolei Wang, Pan Zeng, Xuefeng Tang, Pan Gong, Mao Zhang, Lei Deng, Xinyun Wang

“…The developed hot processing map can precisely predict microstructure evolution. The optimal pre-deformation amount is determined to be 2 %, with a recommended hot processing window defined as 300–400 °C and 0.07–7 s−1.…”
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Nondestructive On-Site Detection of Soybean Contents Based on An Electrothermal MEMS Fourier Transform Spectrometer by Donglin Wang, Peng Wang, Huan Liu, Hongqiong Liu, Jicheng Zhang, Weiguo Liu, Huikai Xie

“…More than 300 samples of soybeans are collected, 80&#x0025; of which are used to establish a prediction model using chemometrics methods. The standard error is no more than 3&#x0025; when using the prediction model to test the remaining 20&#x0025; samples.…”
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Hygienic substantiation of calculating models for prognosis of toxicity of different classes insecticides (second part) by O.P. Vavrinevych, B.I. Shpak, A.M. Antonenko, S.T. Omelchuk, T.I. Zinchenko

“…The purpose of the research is the scientific substantiation and statistical analysis of the calculation models for predicting the toxicity of insecticides of different classes. …”
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Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance by Jingdi Zhang, Wendi Zhan, Haihong Hu, Hongxia Zhu, Bo Hao, Siyu Wang, Zhuo Li, Zhiming Zhang, Taolan Zhang

“…Lasso cox regression analysis and univariate and multivariate Cox analysis were used to process the data, and machine learning algorithm was used to construct breast cancer prognosis model. …”
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Leveraging Function Intersectionality and Multi-Modal Cerebrovascular Reactivity Measures for the Derivation of Individualized Intracranial Pressure Thresholds in Acute Traumatic N... by Kevin Y. Stein, Logan Froese, Alwyn Gomez, Amanjyot Singh Sainbhi, Nuray Vakitbilir, Abrar Islam, Tobias Bergmann, Frederick A. Zeiler

“…PRx-based iICP seems to be superior to both PAx- and RAC-based iICP for predicting long-term outcomes. However, further work is needed to identify the ideal cerebrovascular reactivity thresholds for iICP derivation.…”
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Radio Propagation Models Based on Machine Learning Using Geometric Parameters for a Mixed City-River Path by Allan Dos S. Braga, Hugo A. O. Da Cruz, Leslye E. C. Eras, Jasmine P. L. Araujo, Miercio C. A. Neto, Diego K. N. Silva, Gervasio P. S. Cavalcante

“…This work presents and evaluates the use of geometric parameters of the environment in the prediction of the electric field in mixed city-river type environments, employing two techniques of Machine Learning (ML) as Artificial Neural Networks (ANN) and Neuro-Fuzzy System (NFS). …”
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HMS-PAU-IN: A heterogeneous multi-scale spatiotemporal interaction network model for population analysis units by Xiaorui Yang, Rui Li, Jing Xia, Junhao Wang, Hongyan Li, Nixiao Zou

“…To validate the model, we developed a population prediction model that integrates the multi-scale features of PAUs and introduced Leiden-IES-PMS, a community detection method based on the Leiden algorithm, which integrates internal and external environmental semantics and adopts a proximity merging strategy. …”
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Modeling the service life of temporary airfield operational surfaces under multi-pass aircraft trafficking by R.P. Kinser, T.W. Rushing, A.R. Cisko, Mark E. Barkey, P.G. Allison, J.B. Jordon

“…The proposed framework is then used to predict the rate of subgrade deformation for additional lay patterns, which successfully ranked the performance of each relative to full-scale trafficking experiments. …”
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Dexmedetomidine induces immunogenic cancer cell death and sensitizes tumors to PD-1 blockade by Peng Liu, Guido Kroemer, Oliver Kepp, Jonathan Pol, Liwei Zhao, Lucillia Bezu, Allan Sauvat, Jiani Liu, Killian Carnet Le Provost, Andrea Checcoli

“…A machine learning-based algorithm trained with information on the biological effects and molecular descriptors of analgesics, anesthetics, hypnotics and opioids predicted antitumor effects for dexmedetomidine (DEX). …”
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TCN–Transformer Spatio-Temporal Feature Decoupling and Dynamic Kernel Density Estimation for Gas Concentration Fluctuation Warning by Yanping Wang, Longcheng Zhang, Zhenguo Yan, Jun Deng, Yuxin Huang, Zhixin Qin, Yuqi Cao, Yiyang Wang

“…A flood optimization algorithm (FLA) is used to establish a hyperparameter collaborative optimization framework. …”
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CHILES. IX. Observational and Simulated H i Content and Star Formation of Blue Galaxies in Different Cosmic Web Environments by Nicholas M. Luber, Farhanul Hasan, J. H. van Gorkom, D. J. Pisano, Joseph N. Burchett, Julia Blue Bird, Hansung B. Gim, Kelley M. Hess, Lucas R. Hunt, David C. Koo, Sushma Kurapati, Danielle Lucero, Nir Mandelker, Martin Meyer, Emmanuel Momjian, Daisuke Nagai, Joel R. Primack, Min S. Yun

“…CHILES observes a decline in the H i fraction from filament cores to voids, exactly the opposite of the trend predicted by TNG. CHILES observes an increase in H i fraction at z  = 0.5 → 0 in the voids, while TNG predicts an increase in this time in all environments. …”
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Hybrid Optimization based on Deep Learning Approach for Short-Term Load Forecast of Electricity Demand in Buildings by Charan Sekhar Makula, Ratna Dahiya

“…The performance of the BiLSTM technique is improved by using the optimally determined hyperparameters via a hybrid optimization algorithm that combines particle swarm optimization (PSO) and grey wolf optimization (GWO). …”
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Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography by Ziwei Zhu, Ke Fan, Shuyuan Zhang, Tingting Hu, Jingyi Li, Ze Zhao, Ye Jin, Shuyang Zhang

“…LASSO regression identified predicted LVEF, E/e′ ratio, and age as significant predictors, with AUC values of 0.833 (CR), 0.695 (CH), and 0.938 (EH) for adverse outcomes prediction. …”
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Robust, fully-automated assessment of cerebral perivascular spaces and white matter lesions: a multicentre MRI longitudinal study of their evolution and association with risk of de... by Giuseppe Barisano, Michael Iv, Jeiran Choupan, Melanie Hayden-Gephart, Michael Weiner, Paul Aisen, Ronald Petersen, Clifford R. Jack, William Jagust, John Q. Trojanowki, Arthur W. Toga, Laurel Beckett, Robert C. Green, Andrew J. Saykin, John Morris, Leslie M. Shaw, Enchi Liu, Tom Montine, Ronald G. Thomas, Michael Donohue, Sarah Walter, Devon Gessert, Tamie Sather, Gus Jiminez, Danielle Harvey, Michael Donohue, Matthew Bernstein, Nick Fox, Paul Thompson, Norbert Schuff, Charles DeCarli, Bret Borowski, Jeff Gunter, Matt Senjem, Prashanthi Vemuri, David Jones, Kejal Kantarci, Chad Ward, Robert A. Koeppe, Norm Foster, Eric M. Reiman, Kewei Chen, Chet Mathis, Susan Landau, Nigel J. Cairns, Erin Householder, Lisa Taylor Reinwald, Virginia Lee, Magdalena Korecka, Michal Figurski, Karen Crawford, Scott Neu, Tatiana M. Foroud, Steven Potkin, Li Shen, Faber Kelley, Sungeun Kim, Kwangsik Nho, Zaven Kachaturian, Richard Frank, Peter J. Snyder, Susan Molchan, Jeffrey Kaye, Joseph Quinn, Betty Lind, Raina Carter, Sara Dolen, Lon S. Schneider, Sonia Pawluczyk, Mauricio Beccera, Liberty Teodoro, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Judith L. Heidebrink, Joanne L. Lord, Ronald Petersen, Sara S. Mason, Colleen S. Albers, David Knopman, Kris Johnson, Rachelle S. Doody, Javier Villanueva Meyer, Munir Chowdhury, Susan Rountree, Mimi Dang, Yaakov Stern, Lawrence S. Honig, Karen L. Bell, Beau Ances, John C. Morris, Maria Carroll, Sue Leon, Erin Householder, Mark A. Mintun, Stacy Schneider, Angela Oliver, Daniel Marson, Randall Griffith, David Clark, David Geld-macher, John Brockington, Erik Roberson, Hillel Grossman, Effie Mitsis, Leyla deToledo-Morrell, Raj C. Shah, Ranjan Duara, Daniel Varon, Maria T. Greig, Peggy Roberts, Marilyn Albert, Chiadi Onyike, Daniel D’Agostino, Stephanie Kielb, James E. Galvin, Dana M. Pogorelec, Brittany Cerbone, Christina A. Michel, Henry Rusinek, Mony J. de Leon, Lidia Glodzik, Susan De Santi, P. Murali Doraiswamy, Jeffrey R. Petrella, Terence Z. Wong, Steven E. Arnold, Jason H. Karlawish, David Wolk, Charles D. Smith, Greg Jicha, Peter Hardy, Partha Sinha, Elizabeth Oates, Gary Conrad, Oscar L. Lopez, MaryAnn Oakley, Donna M. Simpson, Anton P. Porsteinsson, Bonnie S. Goldstein, Kim Martin, Kelly M. Makino, M. Saleem Ismail, Connie Brand, Ruth A. Mulnard, Gaby Thai, Catherine Mc Adams Ortiz, Kyle Womack, Dana Mathews, Mary Quiceno, Ramon Diaz Arrastia, Richard King, Myron Weiner, Kristen Martin Cook, Michael DeVous, Allan I. Levey, James J. Lah, Janet S. Cellar, Jeffrey M. Burns, Heather S. Anderson, Russell H. Swerdlow, Liana Apostolova, Kathleen Tingus, Ellen Woo, Daniel H.S. Silverman, Po H. Lu, George Bartzokis, Neill R. Graff Radford, Francine Parfitt, Tracy Kendall, Heather Johnson, Martin R. Farlow, AnnMarie Hake, Brandy R. Matthews, Scott Herring, Cynthia Hunt, Christopher H. van Dyck, Richard E. Carson, Martha G. MacAvoy, Howard Chertkow, Howard Bergman, Chris Hosein, Sandra Black, Bojana Stefanovic, Curtis Caldwell, Ging-Yuek Robin Hsiung, Howard Feldman, Benita Mudge, Michele Assaly, Andrew Kertesz, John Rogers, Dick Trost, Charles Bernick, Donna Munic, Diana Kerwin, Marek Marsel Mesulam, Kristine Lipowski, Chuang Kuo Wu, Nancy Johnson, Carl Sadowsky, Walter Martinez, Teresa Villena, Raymond Scott Turner, Kathleen Johnson, Brigid Reynolds, Reisa A. Sperling, Keith A. Johnson, Gad Marshall, Meghan Frey, Jerome Yesavage, Joy L. Taylor, Barton Lane, Allyson Rosen, Jared Tinklenberg, Marwan N. Sabbagh, Christine M. Belden, Sandra A. Jacobson, Sherye A. Sirrel, Neil Kowall, Ronald Killiany, Andrew E. Budson, Alexander Norbash, Patricia Lynn Johnson, Thomas O. Obisesan, Saba Wolday, Joanne Allard, Alan Lerner, Paula Ogrocki, Leon Hudson, Evan Fletcher, Owen Carmichael, John Olichney, Charles DeCarli, Smita Kittur, Michael Borrie, T.Y. Lee, Rob Bartha, Sterling Johnson, Sanjay Asthana, Cynthia M. Carlsson, Steven G. Potkin, Adrian Preda, Dana Nguyen, Pierre Tariot, Adam Fleisher, Stephanie Reeder, Vernice Bates, Horacio Capote, Michelle Rainka, Douglas W. Scharre, Maria Kataki, Anahita Adeli, Earl A. Zimmerman, Dzintra Celmins, Alice D. Brown, Godfrey D. Pearlson, Karen Blank, Karen Anderson, Robert B. Santulli, Tamar J. Kitzmiller, Eben S. Schwartz, Kaycee M. Sink, Jeff D. Williamson, Pradeep Garg, Franklin Watkins, Brian R. Ott, Henry Querfurth, Geoffrey Tremont, Stephen Salloway, Paul Malloy, Stephen Correia, Howard J. Rosen, Bruce L. Miller, Jacobo Mintzer, Kenneth Spicer, David Bachman, Elizabeth Finger, Stephen Pasternak, Irina Rachinsky, John Rogers, Andrew Kertesz, Dick Drost, Nunzio Pomara, Raymundo Hernando, Antero Sarrael, Susan K. Schultz, Laura L. Boles Ponto, Hyungsub Shim, Karen Elizabeth Smith, Norman Relkin, Gloria Chaing, Lisa Raudin, Amanda Smith, Kristin Fargher, Balebail Ashok Raj

“…Fewer PVS and larger PVS diameter at baseline predicted higher dementia risk and accelerated brain atrophy. …”
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