Capturing spatiotemporal variation in salt marsh belowground biomass, a key resilience metric, through geoinformatics by Kyle D. Runion, Deepak R. Mishra, Merryl Alber, Mark A. Lever, Jessica L. O'Connell

“…We used the BERM machine learning algorithms to evaluate how variables relating to biological, climatic, hydrologic, and physical attributes covaried with these BGB observations. …”
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Using machine learning to identify key predictors of maternal success in sheep for improved lamb survival by Ebru Emsen, Bahadir Baran Odevci, Muzeyyen Kutluca Korkmaz

“…Several machine learning algorithms, including Random Forest, Decision Trees, Logistic Regression, and Support Vector Machines (SVM), were evaluated for predictive accuracy. …”
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Infrared Small Target Detection Based on Double Gray-Values Descend Angle Contrast Measure by Song Guan, Dali Zhou, Xiaodong Wang, Pengji Zhou

“…Finally, by defining a double gray-values descend angle and calculating its tangent quotient, further enhancement of targets is achieved alongside suppression of additional background interference and salt noise. Experimental evaluations were conducted on four publicly available datasets, comparing our proposed approach with seven existing algorithms. …”
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P-68 LIVGUARD, A DEEP NEURAL NETWORK FOR CIRRHOSIS DETECTION IN LIVER ULTRASOUND (USD) IMAGES by DIEGO ARUFE, Pablo Gomez del Campo, Ezequiel Demirdjian, Carlos Galmarini

“…Conflict of interest: No Introduction and Objectives: Differents ultrasound (USD) signs have been described for the diagnosis of cirrhosis. …”
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Screening and validation of diagnostic markers for keloids via bioinformatics analysis by Ze Wang, Bo Hu, Wenfei Li, Tengxiao Ma, Lei Li

“…The aim of this study was to screen diagnostic markers of KD via bioinformatics methods and evaluate their clinical application value. Methods: The GSE44270, GSE145725, GSE7890 and GSE83286 datasets were analyzed in combination with difference analysis and weighted gene coexpression network analysis (WGCNA) and machine learning algorithms, candidate genes related to KD were screened and verified via receiver operating characteristic (ROC) curves and external datasets. …”
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19 Predicting daily PM2.5 in Mexico City: A hybrid spatiotemporal modeling approach by Mike He, Ellen Ren, Iván Gutiérrez-Avila, Itai Kloog

“…We employed machine-learning-based approaches (random forest and gradient boosting algorithms) to downscale satellite measurements and incorporate local sources, then utilized a generalized additive model (GAM) to geographically weight predictions from the initial models. …”
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Comparison of Cuff Leak Test, Laryngeal Ultrasonography, and Videolaryngoscopy for the prediction of post-extubation stridor by Rubina Khullar Mahajan, Apoorva Gupta, Parshotam Lal Gautam, Gunchan Paul, Vikalp Khatri

“…Cuff leak volume (CLV), leak volume fraction ratio (LVFR), and airway column width difference (ACWD) were noted. The grade of peri-laryngeal edema was noted with VL. …”
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Accuracy of warm ischemia time measurement using a surgical intelligence software in partial nephrectomies: A validation study by Archan Khandekar, Joao G. Porto, Jean C. Daher, Pedro F. S. Freitas, Dotan Asselman, Maritza M. Suarez, Mark L. Gonzalgo, Dipen J. Parekh, Sanoj Punnen

“…The platform utilized computer vision algorithms to detect clamp placement and removal, enabling precise WIT measurement. …”
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Modern fixation techniques versus traditional tension band wiring for olecranon fractures: a systematic review and meta-analysis of functional outcomes, healing time, and complicat... by Chengjing Wang, Changqing Li

“…Larger standardized trials are needed to confirm these preliminary conclusions and refine evidence-based treatment algorithms.…”
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Development and validation of interpretable machine learning models for postoperative pneumonia prediction by Bingbing Xiang, Yiran Liu, Shulan Jiao, Wensheng Zhang, Shun Wang, Mingliang Yi

“…This study aimed to develop and validate a predictive model for postoperative pneumonia in surgical patients using nine machine learning methods.ObjectiveOur study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms. By evaluating the performance differences among these machine learning models, this study aims to assist clinicians in early prediction and diagnosis of POP, providing optimal interventions and treatments.MethodsRetrospective data from electronic medical records was collected for 264 patients diagnosed with postoperative pneumonia and 264 healthy control surgical patients. …”
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A systematic review and meta-analysis of utility-based quality of life in chronic kidney disease treatments. by Melanie Wyld, Rachael Lisa Morton, Andrew Hayen, Kirsten Howard, Angela Claire Webster

“…<h4>Background</h4>Chronic kidney disease (CKD) is a common and costly condition to treat. Economic evaluations of health care often incorporate patient preferences for health outcomes using utilities. …”
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Gender Disparities in Artificial Intelligence–Generated Images of Hospital Leadership in the United States by Mia Gisselbaek, MD, Joana Berger-Estilita, MD, PhD, Laurens Minsart, MD, Ekin Köselerli, MD, Arnout Devos, PhD, Francisco Maio Matos, PhD, Odmara L. Barreto Chang, MD, PhD, Peter Dieckmann, PhD, Melanie Suppan, MD, Sarah Saxena, MD, PhD

“…Objective: To evaluate demographic representation in artificial intelligence (AI)–generated images of hospital leadership roles and compare them with real-world data from US hospitals. …”
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Artificial Intelligence Performance in Cardiac Magnetic Resonance Strain Analysis for Aortic Stenosis: Validation with Echocardiography and Healthy Controls by Žygimantas Abramikas, Ieva Jasiukevičiūtė, Giedrė Balčiūnaitė, Sigita Glaveckaitė, Darius Palionis, Nomeda Valevičienė

“…Error rates, segmental, and global myocardial strain differences were assessed between AS patients and the control group. …”
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Prognostic significance of calcium-related genes in lung adenocarcinoma and the role of TNNC1 in macrophage polarization and erlotinib resistance by Jian Feng, Zhe Chen, Gaoming Wang, Yu Yao, Xuewen Min, Jing Luo, Kai Xie

“…A prognostic signature was constructed and validated using external datasets. Differences in immune infiltration and potential mechanisms in LUAD were explored using seven algorithms. …”
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Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic... by Peng Lyu, Na Xie, Xu-peng Shao, Shuai Xing, Xiao-yue Wang, Li-yun Duan, Xue Zhao, Jia-min Lu, Rong-fei Liu, Duo Zhang, Wei Lu, Kai-liang Fan

“…Thereafter, the genes were identified utilizing machine-learning algorithms. The receiver operating characteristic curve was employed to assess the discrimination and effectiveness of the hub genes. …”
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Integration of agronomic information, vegetation indices (VIs), and meteorological data for phenological monitoring and yield estimation of rice (Oryza sativa L.) by Jorge A. Fernandez-Jibaja, Nilton Atalaya-Marin, Yeltsin A. Álvarez-Robledo, Victor H. Taboada-Mitma, Juancarlos Cruz-Luis, Daniel Tineo, Malluri Goñas, Darwin Gómez-Fernández

“…Among the regression algorithms tested, support vector regression (SVR) demonstrated the highest predictive accuracy (R² = 0.81) for the Bellavista variety at the maximum tillering stage. …”
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Quantum <i>κ</i>-Entropy: A Quantum Computational Approach by Demosthenes Ellinas, Giorgio Kaniadakis

“…Third, a simple inter-relation of the von Neumann entropy and the quantum <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>κ</mi></semantics></math></inline-formula>-entropy is worked out and a bound of their difference is evaluated and interpreted. Also the effect on the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>κ</mi></semantics></math></inline-formula>-entropy of quantum noise, implemented as a random unitary quantum channel acting in the system’s density matrix, is addressed and a bound on the entropy, depending on the spectral properties of the noisy channel and the system’s density matrix, is evaluated. …”
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Predicting the Risk of Preterm Birth Throughout Pregnancy Based on a Novel Transcriptomic Signature by Yang Pan, Yuxin Ran, Dongni Huang, Nanlin Yin, Yanqing Wen, Yan Jiang, Yamin Liu, Hongbo Qi

“…It aimed to identify the transcriptomic signature essential for the occurrence of PTB and evaluate its predictive value in early, mid, and late pregnancy and in women with threatened preterm labor (TPTL). …”
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Non-Destructive Monitoring of External Quality of Date Palm Fruit (<i>Phoenix dactylifera</i> L.) During Frozen Storage Using Digital Camera and Flatbed Scanner by Younes Noutfia, Ewa Ropelewska, Zbigniew Jóźwiak, Krzysztof Rutkowski

“…Then, extracted features were used as inputs for pre-established algorithms–groups within WEKA 3.9 software to classify frozen date fruit samples after 0, 2, 4, and 6 months of storage. …”
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A Comparative Analysis of Machine Learning and Pedotransfer Functions Under Varying Data Availability in Two Greek Regions by Panagiotis Tziachris, Panagiota Louka, Eirini Metaxa, Miltiadis Iatrou, Konstantinos Tsiouplakis

“…The current study evaluates the performance of pedotransfer functions (PTFs) and machine learning (ML) algorithms in predicting the soil bulk density (BD) across two distinct regions in Greece—Kozani and Veroia—using both limited and extended sets of soil parameters. …”
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