A Reproducible Method for Donor Site Computed Tomography Measurements in Abdominally Based Autologous Breast Reconstruction by Damini Tandon, MD, Arthur Sletten, MD, PhD, Austin Ha, MD, Gary B. Skolnick, BA, MBA, Paul Commean, BEE, Terence Myckatyn, MD

“…Larger patient cohorts must be leveraged to determine correlations between abdominal CT scan findings and donor site outcomes using machine learning algorithms that generate models for predicting abdominal donor site complications.…”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. Specifically, an optimized You Only Look Once (YOLO) v8n model was developed by integrating a dilation-wise residual–dilated re-parameterization block module, a generalized feature pyramid network, and the Scylla Intersection-over-Union loss function. …”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…Propensity score matching (PSM) and machine learning algorithms were used for confounder adjustment and feature selection.ResultsAfter PSM, 1,429 patients with ARF were included (374 metformin users; 1,055 non-users). …”
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Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH by Qing-Yu Chen, Shu-Min Yin, Ming-Ming Shao, Feng-Shuang Yi, Huan-Zhong Shi

“…The dataset was divided into training and test set with a ratio of 7:3 with 6 machine learning algorithms implemented to diagnosis pleural effusion. …”
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Decoding the diagnostic biomarkers of mitochondrial dysfunction related gene variants in pediatric T cell acute lymphoblastic leukemia by Yunfeng Lu, Xi Yang, Liying Liu, Xiaojun Sun, Xiuli Li, Ping Zhao, Guotao Guan, Yunpeng Dai

“…The intersection of LASSO regression and RF algorithms highlighted two pivotal genes: RNLS and ULK1. …”
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Estimation of soil organic carbon content and dynamics in Mediterranean climate regions considering long-term monthly climatic conditions by Lei Shen, Wei Zhang, Duanqiang Zhai, Shuo Han, Shuang Tian

“…Results showed that the introduction of long-term average monthly climate data significantly improved the prediction accuracy of the models. The R2 value of the RF model was enhanced by 0.22, whilst the R2 of the LightGBM model improved by 0.20–0.21. …”
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Retrotransposon methylation profiles and survival in Black women with high-grade serous ovarian carcinoma by Christelle Colin-Leitzinger, Katherine A. Lawson-Michod, Courtney E. Johnson, Irma M. Vlasac, Sean Yoder, Tania Mesa, Dana Roeber, Chad Huff, Michelle A. T. Hildebrandt, Kristin Haller, Anthony J. Alberg, Elisa V. Bandera, Melissa Bondy, Michele L. Cote, Theresa Hastert, Edward S. Peters, Paul D. Terry, Andrew B. Lawson, Andrew Berchuck, Brooke L. Fridley, Jing-Yi Chern, Jennifer A. Doherty, Jeffrey R. Marks, Joellen M. Schildkraut, Brock C. Christensen, Lucas A. Salas, Lauren C. Peres

“…Methods Methylation levels of LTR, LINE-1, and Alu (type of SINE) in 200 HGSOC tumors were predicted using a random forest approach and clustered using multiple consensus algorithms. …”
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Neutrophil- and Endothelial Cell-Derived Extracellular Microvesicles Are Promising Putative Biomarkers for Breast Cancer Diagnosis by Thayse Batista Moreira, Marina Malheiros Araújo Silvestrini, Ana Luiza de Freitas Magalhães Gomes, Kerstin Kapp Rangel, Álvaro Percínio Costa, Matheus Souza Gomes, Laurence Rodrigues do Amaral, Olindo Assis Martins-Filho, Paulo Guilherme de Oliveira Salles, Letícia Conceição Braga, Andréa Teixeira-Carvalho

“…Machine learning approaches were employed to determine the performance of MVs to identify BC and to propose BC classifier algorithms. <b>Results:</b> Patients with BC had more neutrophil- and endothelial cell-derived MVs than controls before treatment. …”
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An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis by Shuang Wang, Liying Song, Yuanjie Sun, Haonan Zhou, Jia Yao

“…First, the reports of antipsychotics were extracted from the US FDA Adverse Event Reporting System (FAERS), and the signals of AP were detected by four pharmacovigilance algorithms. The gene targets of drugs were predicted using multiple databases. …”
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Hybrid Long Short-Term Memory Wavelet Transform Models for Short-Term Electricity Load Forecasting by Agbassou Guenoukpati, Akuété Pierre Agbessi, Adekunlé Akim Salami, Yawo Amen Bakpo

“…This approach offers significant advantages in reducing algorithmic complexity and effectively processing patterns within the same class of data. …”
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Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning by Yating Zhan, Min Weng, Yangyang Guo, Dingfeng Lv, Feng Zhao, Zejun Yan, Junhui Jiang, Yanyi Xiao, Lili Yao

“…Integrative machine learning combination based on 10 machine learning algorithms was used for the construction of robust signature. …”
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Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool by Juan Francisco Morales, Marian Klose, Yannick Hoffert, Jagdeep T. Podichetty, Jackson Burton, Stephan Schmidt, Klaus Romero, Inish O'Doherty, Frank Martin, Martha Campbell‐Thompson, Michael J. Haller, Mark A. Atkinson, Sarah Kim

“…To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. …”
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Evaluating Material Parameter Influence on Drapability Using VStitcher by Malin Schiller, Soraya Flohr, Jeanne Marisol Delmas, Anja Krüger, Anne-Marie Miene, Patrizia Zimmermann, Lena Wolf, Miriam Seffers, Michelle-Sophie Ruchay-Drammeh, Ulrike Reinhardt, Lilia Sabantina

“…It is a matter not only of generating photo-realistic images in 3D garment simulations, but also of making reliable predictions about the physical behavior of textile materials in order to achieve realistic outcomes. …”
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Mapping the global risk of chikungunya virus endemicity and autochthonous transmission following importation by Yu-Feng Yang, Yun-Bo Qiu, Qiang Xu, Rui-Cheng Gao, Tian Tang, Yao Tian, Yan-He Wang, Sheng-Hong Lin, Yun-Dong Shi, Long-Tao Chen, Yan Zhang, Jun Ma, Chen-Long Lv, Guo-Lin Wang, Hai-Feng Pan, Wei Liu, Li-Qun Fang

“…Three machine learning algorithms were utilized to analyze the ecological factors associated with CHIKV occurrences in regions characterized by endemic or autochthonous transmission following importation. …”
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Machine learning and response surface methodology forecasting comparison for improved spray dry scrubber performance with brine sludge-derived sorbent by B.J. Chepkonga, L. Koech, R.S. Makomere, H.L. Rutto

“…The response surface methodology (RSM) model also proved to be a reliable forecasting tool, indicating its potential as a practical alternative to complex algorithmic computations in scenarios with limited raw data.…”
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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

“…In addition, MD is a powerful method for predicting mechanical, thermal, and electronic properties of nanomaterials in different environments. …”
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Experimental validation of cuproptosis-associated molecular signatures and their immunological implications in pulmonary tuberculosis by Xiaofang Liu, Xiaofang Liu, Qianqian Ma, Zhiming Li, Yong Xue, Jie Mi, Yuxi Li, Chunfeng Bai, Donglin Guo, Yinping Liu, Yan Liang, Jianqin Liang, Xueqiong Wu

“…Hub CRGs were screened out via least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms. Diagnostic models were subsequently constructed and validated. …”
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Pharmacological potential of 6,11-dihydro[1,2,4]triazolo[4’,3’:1,6]-pyrido[3,4-b]-5-carboxylic acid and its esters by S. O. Fedotov, A. S. Hotsulia

“…The molecular docking method, based on computational algorithms, has been used to predict and study interactions, including the identification of potential binding sites, estimation of energy parameters and spatial configuration of molecules. …”
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Molecular subtype of recurrent implantation failure reveals distinct endometrial etiology of female infertility by Jing Yang, Lingtao Yang, Ying Zhou, Fengyang Cao, Hongkun Fang, Huan Ma, Jun Ren, Chunyu Huang, Lianghui Diao, Qiyuan Li, Qionghua Chen

“…A molecular classifier (MetaRIF) was developed using the optimal F-score from 64 combinations of machine learning algorithms. Candidate therapeutic compounds were predicted using the Connectivity Map (CMap) database. …”
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Editorial by Bulent Cavas

“…The eighth article, “Prediction of Middle School Students’ Recycling Behaviors with Machine Learning Algorithms,” by Mustafaoğlu and Alkan (Türkiye), applies machine learning techniques to identify factors predicting students&#39; recycling behavior. …”
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