The identification and validation of histone acetylation-related biomarkers in depression disorder based on bioinformatics and machine learning approaches by Lu Zhang, Lu Zhang, YuJing Lv, Mengqing Ma, Jile Lv, Jie Chen, Shang Lei, Yi Man, Guimei Xing, Yu Wang

“…BackgroundSome studies indicated that histone modification may be involved in depression disorder (DD). The maintenance of the histone acetylation state is the work of histone acetyltransferase (HAT) and histone deacetylase (HDAC), which is thought to be a potential diagnostic biomarker of depression. …”
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Rethinking the Paradigm of Using Ps for Diagnosing Compartment Syndrome by Yasser Bouklouch, BSc, MPH, July Agel, MA, ATC, William T. Obremskey, MD, MPH, MMHC, Andrew H. Schmidt, MD, Kathy Liu, MB, ChB, Jerald R. Westberg, MPH, Matthew Zakariah, BSc, Eli Bunzel, MD, Greer Henry, MSc, Andres Fidel Diaz, MD, Thierry Bégué, MD, Mitchell Bernstein, MD, Edward J. Harvey, MDCM, MSc

“…Objective measures such as continuous pressure or a physiologic marker of ischemia may be better indications for compartment syndrome. …”
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Machine Learning Models for Predicting Abnormal Brain CT Scan Findings in Mild Traumatic Brain Injury Patients by Amirmohammad Toloui, Amir Ghaffari Jolfayi, Hamed Zarei, Arash Ansarian, Amir Azimi, Seyed Mohammad Forouzannia, Rosita Khatamian Oskooi, Gholamreza Faridaalaee, Shayan Roshdi Dizaji, Seyed Ali Forouzannia, Seyedeh Niloufar Rafiei Alavi, Mohammadreza Alizadeh, Hadis Najafimehr, Saeed Safari, Alireza Baratloo, Mostafa Hosseini, Mahmoud Yousefifard

“…This study aimed to develop and optimize machine learning (ML) algorithms to predict abnormal brain computed tomography (CT) scans in patients with mild TBI. …”
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Changes in soil pH on the Tibetan Plateau from the 1980 s to 2020 s by Lirong Zhao, Bo Pang, Jiangtao Hong, Xinxin Zhang, Jinmei Li, Xiaodan Wang

“…Here, we utilized resampling methods and machine learning algorithms to explore the spatiotemporal variations and driving factors of soil pH on the Tibetan Plateau from the 1980 s to 2020 s. …”
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MultiModal Ensemble Approach Leveraging Spatial, Skeletal, and Edge Features for Enhanced Bangla Sign Language Recognition by Khan Abrar Shams, Md. Rafid Reaz, Mohammad Ryan Ur Rafi, Sanjida Islam, Md. Shahriar Rahman, Rafeed Rahman, Md. Tanzim Reza, Mohammad Zavid Parvez, Subrata Chakraborty, Biswajeet Pradhan, Abdullah Alamri

“…The CNN models are combined using nine distinct ensemble meta-learning algorithms, with five of them being modifications of averaging and voting techniques. …”
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Inertial-Based Dual-Task Gait Normalcy Index at Turns: A Potential Novel Gait Biomarker for Early-Stage Parkinson’s Disease by Lin Meng, Xiaofei Zhang, Yu Shi, Xinge Li, Jun Pang, Lei Chen, Xiaodong Zhu, Rui Xu, Dong Ming

“…However, few studies have explored gait deviation evaluation algorithms under a complex dual task that reflect disease specificity. …”
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Predicting 30-Day Venous Thromboembolism Following Total Joint Arthroplasty: Adjusting for Trends in Annual Length of Stay by Johnathan R. Lex, MBChB, MASc, Robert Koucheki, MD, MEng, Aazad Abbas, MD, Jesse I. Wolfstadt, MD, MSc, FRCSC, FAAOS, Alexander S. McLawhorn, MD, MBA, Bheeshma Ravi, MD, PhD, FRCSC

“…Development of more accurate machine learning models for VTE prediction may improve risk stratification, prevention, and monitoring for arthroplasty patients.…”
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Identification of a potential miRNA–mRNA regulatory network for ischemic stroke by using bioinformatics methods: a retrospective study based on the Gene Expression Omnibus database... by Zhaoying Chen, Xiaodan Zhang, Xiangjun Qi, Jiyuan Zheng, Niancai He, Bohui Zheng, Nan Zhong, Chengcheng Ji, Yulan Jin, Hu Yu, Weinv Fan, Guoming Chen

“…Bioinformatics analyses, including differential expression analysis and machine learning algorithms, were employed to identify key miRNAs and their target mRNAs. …”
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Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer by Yanliang Chen, Chan Zhou, Xiaoqiao Zhang, Min Chen, Meifang Wang, Lisha Zhang, Yanhui Chen, Litao Huang, Junjun Sun, Dandan Wang, Yong Chen

“…Its clinical routine use may assist clinicians in selecting more rational practices for individuals, which is important for improving the prognosis of NSCLC patients. …”
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Pediatric anaphylaxis in the emergency department: Performances of dynamic tryptase measurement by Constance Gonzalez, MD, Meng Sun, MSc, Aurélie Morand, MD, PhD, Philippe Minodier, MD, Marc Leone, MD, PhD, Jean-Christophe Dubus, MD, PhD, Joana Vitte, MD, PhD, Moïse Michel, PharmD, PhD

“…Objective: We assessed the diagnostic accuracy of the consensus formula and alternative algorithms for interpreting tryptase levels in pediatric patients with suspected anaphylaxis. …”
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γ‐Glutamyl Transferase and Long‐Term Survival in the SYNTAXES Trial: Is It Just the Liver? by Kai Ninomiya, Patrick W. Serruys, Scot Garg, Shigetaka Kageyama, Nozomi Kotoku, Shinichiro Masuda, Pruthvi C. Revaiah, Neil O'leary, Arie Pieter Kappetein, Michael J. Mack, David R. Holmes, Piroze M. Davierwala, Friedrich W. Mohr, Daniel J. F. M. Thuijs, Yoshinobu Onuma

“…In patients with elevated GGT, strong secondary prevention may be required after revascularization and must be studied prospectively. …”
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Recent Developments to the ANSWERS® Monte Carlo Codes MONK® and MCBEND® by Fildes Jessica, Richards Simon, Bird Adam, Cox Andrew, Fry Timothy, Hanlon David, Jones Brian, Long David, Tantillo Francesco, Wright George, Hiles Richard

“…IGES-formatted CAD geometries may be imported into MONK and MCBEND and approximated as a set of triangular surface polygons in a new Fractal Geometry body. …”
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A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…We also define bottom-up parsing algorithms to recommend the suitable crowd prevention plan w.r.t. the crowd level. …”
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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…Abdominal fat (AF) in hens impacts egg production and may reflect poor feed efficiency, meaning that dynamic monitor of AF changes facilitate to optimize feeding management and production efficiency. …”
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Differing Effects of Alcohol Use on Epigenetic and Brain Age in Adult Children of Parents with Alcohol Use Disorder by Jamie L. Scholl, Kami Pearson, Kelene A. Fercho, Austin J. Van Asselt, Noah A. Kallsen, Erik. A. Ehli, Kari N. Potter, Kathleen A. Brown-Rice, Gina L. Forster, Lee A. Baugh

“…We examined structural brain differences and applied machine learning algorithms to predict biological brain and DNA methylation ages to investigate differences and determine any accelerated aging between these groups. …”
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Bipolar disorders and creativity: the roles of ambition, effort-based decision-making, and exploration by Samson Tse, Sheri L. Johnson, Chong Ho Yu, Winnie Yuen, Iris Lo, Luke Clark, Luke Clark, Erin E. Michalak, Erin E. Michalak, Manon Ironside, Kiana Modavi

“…However, decision tree algorithms revealed multivariate contributors to creative accomplishments. …”
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Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female b... by Ricardo Gonzalez, Peyman Nejat, Ashirbani Saha, Clinton J.V. Campbell, Andrew P. Norgan, Cynthia Lokker

“…Increasing the availability of validation datasets and implementing standardized methods and reporting protocols may facilitate future analyses.…”
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In Silico Analysis of Coding/Noncoding SNPs of Human RETN Gene and Characterization of Their Impact on Resistin Stability and Structure by Lamiae Elkhattabi, Imane Morjane, Hicham Charoute, Soumaya Amghar, Hind Bouafi, Zouhair Elkarhat, Rachid Saile, Hassan Rouba, Abdelhamid Barakat

“…Stability analysis predicted 9 nsSNPs (I32S, C51Y, G58E, G58R, C78S, G79C, W98C, C103G, and C104Y) which can decrease protein stability with at least three out of the four algorithms used in this study. These nsSNPs were chosen for structural analysis. …”
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Artificial Intelligence−Driven Analysis Identifies Anterior Cruciate Ligament Reconstruction, Hip Arthroscopy and Femoroacetabular Impingement Syndrome, and Shoulder Instability as... by Henry B.G. Baird, B.S., William Allen, M.D., Mauricio Gallegos, M.D., Cody C. Ashy, M.D., Harris S. Slone, M.D., W. Michael Pullen, M.D.

“…It will also allow us to identify research gaps that may need to be addressed.…”
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Role of inflammation-related genes as prognostic biomarkers and mechanistic implications in idiopathic pulmonary fibrosis by Bing Bai, Bing Bai, Bing Bai, Wenfei Zhao, Fazhan Li, Yang Mi, Pengyuan Zheng

“…Unsupervised clustering algorithms were used to classify IPF samples, followed by weighted gene co-expression network analysis (WGCNA) to identify highly correlated genes. …”
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