Definition, management, and training in impacted fetal head at cesarean birth: a national survey of maternity professionals by Katie Cornthwaite, Pauline Hewitt, Jan W. van derScheer, Imogen A. F. Brown, Jenni Burt, Eliane Dufresne, Mary Dixon‐Woods, Tim Draycott, ABC Contributor Group, Thiscovery Authorship Group, Rachna Bahl

“…These findings can inform a program of work to improve care, including use of structured management algorithms and simulation‐based multi‐professional training.…”
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Diagnosis and detection of bone fracture in radiographic images using deep learning approaches by Theyazn Aldhyani, Zeyad A. T. Ahmed, Bayan M. Alsharbi, Sultan Ahmad, Sultan Ahmad, Mosleh Hmoud Al-Adhaileh, Ahmed Hassan Kamal, Mohammed Almaiah, Jabeen Nazeer

“…By addressing these challenges, we can further improve DL models for fracture detection. This article tackles the limitations of existing methods for fracture detection and diagnosis and proposes a system that improves accuracy.ConclusionThe findings lay the foundation for future improvements to radiographic systems used in bone fracture diagnosis.…”
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GRRIS: A Real-time Intrasite Observation Scheduling Scheme for Distributed Survey Telescope Arrays by Yajie Zhang, Ce Yu, Chao Sun, Yi Hu, Zhaohui Shang, Jizeng Wei, Xu Yang

“…Through numerical simulations with real-world scenarios, GRRIS can achieve up to a 22% solution improvement over the most competitive scheme. It offers better scalability and subsecond decision speed, meeting the needs of observation scheduling control for future distributed telescope arrays.…”
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Potassium Fulvate Alleviates Salinity and Boosts Oat Productivity by Modifying Soil Properties and Rhizosphere Microbial Communities in the Saline–Alkali Soils of the Qaidam Basin... by Jie Wang, Xin Jin, Xinyue Liu, Yunjie Fu, Kui Bao, Zhixiu Quan, Chengti Xu, Wei Wang, Guangxin Lu, Haijuan Zhang

“…Structural equation modeling further showed that PF mitigates salinity chiefly by improving soil physicochemical properties (path coefficient = −0.77; <i>p</i> < 0.001), with microbial assemblages acting as key intermediaries. …”
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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

“…Interpretation: These robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia. …”
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A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization by Md. Saddam Hossain, Md. Parvez Khandocar, Farzana Akter Riti, Md. Yeakub Ali, Prithbey Raj Dey, S M Jahurul Haque, Amira Metouekel, Atrsaw Asrat Mengistie, Mohammed Bourhia, Farid Khallouki, Khalid S. Almaary

“…Software can adapt and improve with new information. Imaging scans leverage pattern recognition to predict outcomes, diagnose disorders, and suggest treatments. …”
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Enhanced estimation of reference evapotranspiration using hybrid deep learning models and remote sensing variables by Tze Ying Fong, Yuk Feng Huang, Ren Jie Chin, Chai Hoon Koo

“…This study aims to develop ETo estimation models using deep learning algorithms with remote sensing variables as the input variables at Pulau Langkawi and Kuantan stations, located in Peninsular Malaysia. …”
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Identification of hub genes for the diagnosis associated with heart failure using multiple cell death patterns by Hua‐jing Yuan, Hui Yu, Yi‐ding Yu, Xiu‐juan Liu, Wen‐wen Liu, Yi‐tao Xue, Yan Li

“…This study aims to identify the hub genes associated with HF through PCD in order to better understand the pathogenesis of HF and improve its diagnosis and treatment. Methods and results The gene expression dataset of HF was obtained from the GEO database. …”
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Sweet Potato Yield Prediction Using Machine Learning Based on Multispectral Images Acquired from a Small Unmanned Aerial Vehicle by Kriti Singh, Yanbo Huang, Wyatt Young, Lorin Harvey, Mark Hall, Xin Zhang, Edgar Lobaton, Johnie Jenkins, Mark Shankle

“…Classical machine learning (ML) approaches and tree-based algorithms, like XGBoost and Random Forest, are implemented. …”
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Predicting cardiotoxicity in drug development: A deep learning approach by Kaifeng Liu, Huizi Cui, Xiangyu Yu, Wannan Li, Weiwei Han

“…In this study, we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds, with the aim of improving prediction accuracy and efficiency. We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. …”
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Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction by Zhengbiao Hu, Shuangshan Bu, Kai Wang, Qianqian Cao, Huanhuan Zheng, Jie Yang, Shanshan Chen, Yuemeng Wu, Wenkai Ren, Chenlei He

“…In this study, multiple machine learning algorithms were used to develop a non-invasive and improved model for the diagnosis of IgAN. …”
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Proteomic analysis of blood plasma as a tool for personalized diagnosis of lung adenocarcinoma by D. N. Korobkov, A. S. Kononikhin, S. D. Semenov, H. L. Kordzaya, A. G. Brzhozovskiy, A. E. Bugrova, E. Yu. Vasilieva, D. Yu. Kanner, E. N. Nikolaev, A. A. Komissarov

“…Despite significant success in the diagnosis and treatment of tumors, the five-year survival rate for lung cancer is only 19 % and has not improved significantly in recent decades, which is mainly associated with late detection of the disease. …”
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Applications of molecular dynamics in nanomaterial design and characterization - A review by Md. Aminul Islam, S M Maksudur Rahman, Juhi Jannat Mim, Safiullah Khan, Fardin Khan, Md. Ahadul Islam Patwary, Nayem Hossain

“…Recent advances, such as improved multiscale modeling and computational algorithms and real-time simulations, shed light onto MD processes of revolutionizing nanotechnology. …”
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Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks? by Jowaria Khan, Rana Elfakharany, Hiba Saleem, Mahira Pathan, Emaan Shahzad, Salam Dhou, Fadi Aloul

“…System administrators are responsible for recreating whole attack scenarios and developing improved intrusion detection systems since the systems at present are still designed to generate alerts for only single attacks with little to no correlation. …”
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Two-dimensional differential form of distributed Xinanjiang model by J. Zhao, Z. Liang, V. P. Singh, V. P. Singh, V. P. Singh, T. Wen, Y. Hu, B. Li, J. Wang

“…Our results suggested that (a) numerical errors in the existing distributed Xinanjiang model are significant and may be exacerbated by a potential terrain amplification effect, which could be effectively controlled by the fully coupled numerical framework within the TDD-XAJ model; (b) the 2D slope concentration methods showed enhanced terrain capture ability and eliminated the reliance on the flow direction algorithms used in 1D methods; and (c) the TDD-XAJ model exhibited improved simulation capabilities compared to the existing model when applied in the Tunxi watershed, particularly for flood volume. …”
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SA-MARL: Novel Self-Attention-Based Multi-Agent Reinforcement Learning With Stochastic Gradient Descent by Rabbiya Younas, Hafiz Muhammad Raza Ur Rehman, Ingyu Lee, Byung-Won On, Sungwon Yi, Gyu Sang Choi

“…Second, to address the local optima problem in MARL algorithms, we leverage the Grey Wolf Optimizer for weight and bias selection, adding a stochastic element for improved optimization. …”
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Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…The developed sigmoid (SG) activation function-based ELM (SG-ELM) shows performance improvement over sine (SI) function-based ELM (SI-ELM) model and PS-SVR model with an improvement of 79.25 % and 89.4 % using root mean square error (RMSE) performance measuring parameter. …”
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INCOIS air-sea Flux Reference System onboard ORV Sagar Nidhi: overview and initial results by B. Praveen Kumar, Abhijith Raj, Abhijith Raj, Asish K. Sasidharan, Asish K. Sasidharan, N. Sureshkumar, A. A. Gnanaraj, Deepak Sankar, K. Ramasundaram, Venkata Jampana, E. Pattabhi Rama Rao

“…Data from this system are useful for validating model outputs and satellite observations, refining flux parameterizations, marine boundary layer studies, and improving air-sea interaction models. INCOIS-FRS represents a first step toward equipping more oceanographic platforms, both crewed and uncrewed, with flux reference units. …”
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Machine vision-based detection of key traits in shiitake mushroom caps by Jiuxiao Zhao, Jiuxiao Zhao, Wengang Zheng, Wengang Zheng, Yibo Wei, Yibo Wei, Qian Zhao, Qian Zhao, Jing Dong, Jing Dong, Xin Zhang, Xin Zhang, Mingfei Wang, Mingfei Wang

“…In practical applications, this method improves the breeding process by rapidly and non-invasively assessing key traits such as the size and color of shiitake mushroom caps, which helps in efficiently screening strains and reducing human errors. …”
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Identification and validation of glucocorticoid receptor and programmed cell death-related genes in spinal cord injury using machine learning by Feng Lu, Yingying Liu, Zhen Chen, Shuning Chen, Weidong Liang, Fuzhou Hua, Maolin Zhong, Lifeng Wang

“…In this study, we identified GR- and PCD-related DEGs in SCI and constructed a diagnostic model that may improve understanding of SCI molecular mechanisms and inform future investigations of glucocorticoid use.…”
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