The molecular characteristics of DNA damage and repair related to P53 mutation for predicting the recurrence and immunotherapy response in hepatocellular carcinoma by Jiayao Ma, Diya Tang, Guangzu Cui, Xiangyang Zhang, Xinwen Wang, Yin Li, Erya Hu, Xin Zhou, Haicong Liu, Qingping Peng, Changjing Cai, Xiangying Deng, Shan Zeng, Yihong Chen, Zemin Xiao

“…Next, among the 173 combinations of algorithms and parameters, CoxBoost + RSF, Lasso [fold = 10] + RSF, and Lasso [fold = 50] + RSF demonstrated the best performance. …”
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Machine learning-based prediction model for recurrence after radiofrequency catheter ablation in patients with atrial fibrillation by Lujing Nie, Tianwei Zhang, Wenhua Wang, Xuefu Han, Meng Liu, Shujie Zhang, Wenjiu Feng, Yujie Wang, Yanbo Chen

“…Patients were randomly assigned to either a training cohort (70%) or a testing cohort (30%). Four ML algorithms were employed to develop prediction models. …”
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Deep sea spy: An online citizen science annotation platform for science and ocean literacy by Marjolaine Matabos, Pierre Cottais, Riwan Leroux, Yannick Cenatiempo, Charlotte Gasne-Destaville, Nicolas Roullet, Jozée Sarrazin, Julie Tourolle, Catherine Borremans

“…Although deep learning offers an alternative to human processing, training algorithms requires large annotated reference datasets. …”
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A Comparative Study of Machine Learning Techniques for Predicting Mechanical Properties of Fused Deposition Modelling (FDM)-Based 3D-Printed Wood/PLA Biocomposite by Prashant Anerao, Atul Kulkarni, Yashwant Munde, Namrate Kharate

“…The dataset has been carefully prepared to facilitate machine learning for both training and testing, and it contains the experimental results and associated process parameters. …”
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What has changed in the attitude of health workers towards vaccination after the pandemic COVID-19 by S. M. Kharit, L. V. Romanov, Yu. E. Konstantinova, S. A. Bogdan

“…To improve the work on vaccination, 44.5% indicated the need for information on the official websites of the Ministry of Health of the Russian Federation, FMBA, Rospotrebnadzor and RoszdravnadzorConclusion The results of the survey indicate the need to modernize the system of training in vaccination of medical workers of various specialties, the development of new forms of information presentation, the use of official websites, the development of algorithms for communicating with the population on adherence to vaccination,…”
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Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma by Xiang Xiong, Wen Liu, Chuan Yao

“…Subsequently, we employed the training group to construct the prognostic model and utilized the testing group to validate the model’s accuracy. …”
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Early prediction of progression-free survival of patients with locally advanced nasopharyngeal carcinoma using multi-parametric MRI radiomics by Lian Jian, Cai Sheng, Huaping Liu, Handong Li, Pingsheng Hu, Zhaodong Ai, Xiaoping Yu, Huai Liu

“…Pearson correlation analysis and recursive feature elimination or Relief were used for identifying features associated with progression-free survival (PFS). Five machine learning algorithms with cross-validation were compared to develop the optimal single-layer and fusion radiomic models. …”
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Multi-Omics Identification of <i>Fos</i> as a Central Regulator in Skeletal Muscle Adaptation to Long-Term Aerobic Exercise by Chaoyang Li, Xinyuan Zhu, Yi Yan

“…Key feature genes were screened using Lasso regression, SVM-RFE, and Random Forest machine learning algorithms, validated by RT-qPCR, and refined through PPI network analysis. …”
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Transformer-Based Fast Mole Fraction of CO2 Retrievals from Satellite-Measured Spectra by Wei Chen, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang

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The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea by Rafael Rodrigues dos Santos, Matheo Bellini Marumo, Alan Luiz Eckeli, Helio Cesar Salgado, Luiz Eduardo Virgílio Silva, Renato Tinós, Rubens Fazan

“…The Apnea-Hypopnea Index (AHI) was used to categorize into severity classes of OSA (normal, mild, moderate, severe) to train multiclass or binary (normal-to-mild and moderate-to-severe) classification models, using the Random Forest (RF) algorithm. …”
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The Legal Challenges of Implementing AI in Emergency Departments by Shaghayegh Rahmani, Sahar Azamghasemzadeh

“…Additionally, AI systems used in healthcare must be designed with robust security measures to prevent data breaches and ensure the integrity of patient information (1). AI algorithms are often perceived as unbiased tools, but if trained on biased or incomplete data, they can inadvertently perpetuate discrimination or inequality in healthcare outcomes (2). …”
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Comparison of 7 artificial intelligence models in predicting venous thromboembolism in COVID-19 patients by Indika Rajakaruna, Mohammad Hossein Amirhosseini, Mike Makris, Mike Laffan, Yang Li, Deepa J. Arachchillage

“…Methods: We used feature ranking through recursive feature elimination with AI algorithms (logistic regression and random forest classifier) and standard statistical methods to identify the significant factors that contribute to developing VTE in COVID-19 patients using a large dataset from “Coagulopathy associated with COVID-19,” a multicenter observational study. …”
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MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects by Domenico Lofù, Paolo Sorino, Tommaso Colafiglio, Caterina Bonfiglio, Rossella Donghia, Gianluigi Giannelli, Angela Lombardi, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci

“…This selection is achieved through Recursive Feature Elimination (RFE) using a Random Forest (RF) to train Machine Learning (ML) algorithms and provide a mortality risk (Yes/No) output. …”
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Reducing the acquisition time for magnetic resonance imaging using super-resolution image generation and evaluating the accuracy of hippocampal volumes for diagnosing Alzheimer’s d... by Nobukiyo Yoshida, Nobukiyo Yoshida, Hajime Kageyama, Hajime Kageyama, Hiroyuki Akai, Satoshi Kasai, Satoshi Kasai, Kei Sasaki, Noriko Sakurai, Naoki Kodama

“…Network training was performed using a scaled image (64 × 64) down-sampled from the original image as the input image and paired with the original high-resolution (256 × 256) supervised image. …”
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Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma by Liangyu Zhang, Liangyu Zhang, Jianshen Zeng, Jianshen Zeng, Xun Zhang, Xun Zhang, Menglong Zhang, Menglong Zhang, Yilin Lin, Yilin Lin, Fancai Lai, Fancai Lai

“…The training set, TCGA-LUAD, along with SNV and CNV data, was obtained from the TCGA database. …”
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Integrating machine learning with mendelian randomization for unveiling causal gene networks in glioblastoma multiforme by Lixin Du, Pan Wang, Xiaoting Qiu, Zhigang Li, Jianlan Ma, Pengfei Chen

“…Methods This study employed a comprehensive analysis approach integrating 113 machine learning algorithms with Mendelian Randomization (MR) analysis to investigate the molecular underpinnings of GBM. …”
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Automated diagnosis of respiratory diseases from lung ultrasound videos ensuring XAI: an innovative hybrid model approach by Arefin Ittesafun Abian, Mohaimenul Azam Khan Raiaan, Asif Karim, Sami Azam, Nur Mohammad Fahad, Niusha Shafiabady, Kheng Cher Yeo, Friso De Boer

“…The eleven-ablation case study reduced training costs and redundancy. K-fold cross-validation and accuracy-loss curves demonstrated model generalization. …”
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Cervical cancer prediction using machine learning models based on routine blood analysis by Jie Su, Hui Lu, Ruihuan Zhang, Na Cui, Chao Chen, Qin Si, Biao Song

“…Age, clinical diagnosis information and 22 blood cell analysis results were considered. Four different algorithms were applied to construct a model for estimating the likelihood of CC occurrence. …”
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Multimodal AI for Home Wound Patient Referral Decisions From Images With Specialist Annotations by Reza Saadati Fard, Emmanuel Agu, Palawat Busaranuvong, Deepak Kumar, Shefalika Gautam, Bengisu Tulu, Diane Strong

“…Additionally, to interpret DM-WAT&#x2019;s recommendations, the Score-CAM and Captum interpretation algorithms provided insights into the specific parts of the image and text inputs that the model focused on during decision-making.…”
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Digital transformation of modern corporation management tools: the current state and development paths by V. A. Laptev, S. Yu. Chucha, D. R. Feyzrakhmanova

“…In addition, issues related to professional training / retraining of personnel capable of working with modern technologies are of importance.Conclusions. …”
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