Explainable deep learning approach for recognizing “Egyptian Cobra” bite in real-time by Elhoseny Mohamed, Hassan Ahmed, Shehata Marwa H., Kayed Mohammed

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Comparison of Random Survival Forest Based‐Overall Survival With Deep Learning and Cox Proportional Hazard Models in HER‐2‐Positive HR‐Negative Breast Cancer by Wenqi Cai, Yan Qi, Linhui Zheng, Huachao Wu, Chunqian Yang, Runze Zhang, Chaoyan Wu, Haijun Yu

“…Predictive models were developed using five feature sets and three algorithms (Cox PH, RSF, DeepSurv), with feature selection optimized via Concordance index (C‐index). …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…<h4>Methods</h4>Gradient Boosted Decision Tree, Deep and Convolutional Neural Network classifiers were implemented and trained on the National COVID Cohort Collaborative (N3C) data repository to predict the patients' outcome of death or discharge. …”
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Giant pseudoangiomatous stromal hyperplasia of breast: Management challenge of gigantomastia with ptosis by Uma Krishnaswamy, K Balachandar, Thulasilingam Kathirazhagan

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Automatic recognition and differentiation of pulmonary contusion and bacterial pneumonia based on deep learning and radiomics by Tie Deng, Junbang Feng, Xingyan Le, Yuwei Xia, Feng Shi, Fei Yu, Yiqiang Zhan, Xinghua Liu, Chuanming Li

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A novel smart surveillance approach to strengthen health facility-based disease surveillance in Tanzania by Ms Happy Mkali, MD Alix Miauton, Dr. Alexandra Kulinkina, Ms. Magreth Joram, MD Caroline Enos, Mr. Lazar Pavicevic, Mr. Vincent Faivre, Dr. MD Rainer Tan, Dr. Sabine Renggli, Ms. Theopista Lotto, Mr. Sinamgoda Ngailla, MD Godfrey Kavishe, Mr. Ibrahim Mtebene, Mr. Peter Agrea, MD Lameck Luwanda, Mr Geofrey Ashery, MD Chacha Mangu, Dr. MD Nyanda Ntinginya, Prof. Dr. Honorati Masanja, Prof. Dr. MD Isabella Eckerle, Prof. Dr. MD Valerie D'Acremont

“…Methods: An electronic clinical decision support algorithm (CDSA) was provided to healthcare workers to guide them during consultations with children aged 1 day to 14 years. …”
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Intra- and peritumoral radiomics nomogram based on DCE-MRI for the early prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer by Yun Zhu, Shuni Zhang, Wei Wei, Li Yang, Lingling Wang, Ying Wang, Ye Fan, Haitao Sun, Zongyu Xie

“…The CM is constructed based on three independent risk factors: estrogen receptor (ER), Ki-67, and breast edema score (BES). …”
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The spatiotemporal distribution patterns and impact factors of bird species richness: A case study of urban built-up areas in Beijing, China by Zheran Zhai, Siyao Liu, Zimeng Li, Ruijie Ma, Xiaoyu Ge, Haidong Feng, Yang Shi, Chen Gu

“…Additionally, this study employed three tree-based machine learning algorithms—Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—to investigate the influence of environmental factors on bird species distribution within urban built-up areas. …”
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Research on the spatial layout of the elderly care industry based on explainable machine learning: A case study of Hangzhou(基于可解释性机器学习的养老产业空间布局研究)... by 曾笑奇(ZENG Xiaoqi), 赵秋皓(ZHAO Qiuhao), 冯友建(FENG Youjian)

“…Utilizing data from the Seventh National Population Census and POI data, we compare the prediction accuracy of three machine learning models—decision tree (DT), random forest (RF), and extreme gradient boosting tree (XGBoost). …”
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Epidemiology of inflammatory bowel disease in Mexico and Colombia: Analysis of health databases, mathematical modelling and a case-series study. by Agustín Ciapponi, Sacha Alexis Virgilio, Mabel Berrueta, Natalie Claire Soto, Álvaro Ciganda, Moisés Freddy Rojas Illanes, Briseida Rubio Martinez, Johana Gamba, Carlos Arturo González Salazar, José Nicolás Rocha Rodríguez, Bruno Scarpellini, Ana María Bravo Perdomo, Gerardo Machnicki, Leandro Aldunate, Juan De Paula, Ariel Bardach

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CONCEPT OF FINANCIAL FLOW MANAGEMENT OF ENTERPRISE CORPORATE SECURITY SYSTEM by Olena Sergienko, Nataliia Volosnikova, Natalia Reshetniak, Maryna Mashchenko, Valeria Baranova

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Multispectral Sensors and Machine Learning as Modern Tools for Nutrient Content Prediction in Soil by Rafael Felippe Ratke, Paulo Roberto Nunes Viana, Larissa Pereira Ribeiro Teodoro, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro, Dthenifer Cordeiro Santana, Carlos Eduardo da Silva Santos, Alan Mario Zuffo, Jorge González Aguilera

“…The models tested were linear regression, random forest (RF), reptree M5P, multilayer preference neural network, and decision tree algorithms, with the correlation coefficient (r) and mean absolute error (MAE) used as accuracy parameters. …”
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Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes by ZHANG Zihang, XING Bo, MA Zhongqing, HU Yanjun, ZHANG Zhixiao, YUAN Shizhen, LU Rufei, CHEN Yingquan, WANG Shurong*

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Machine Learning-Based Prediction Model for Multidrug-Resistant Organisms Infections: Performance Evaluation and Interpretability Analysis by Zhao W, Sun P, Li W, Shang L

“…Six machine learning algorithms—Neural Networks, Random Forests, Support Vector Machines, Logistic Regression, Decision Trees, and Gaussian Naive Bayes—were evaluated based on AUC, accuracy, and calibration curves. …”
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Development and validation of a nomogram for predicting refractory peritoneal dialysis related peritonitis by Qiqi Yan, Guiling Liu, Ruifeng Wang, Dandan Li, Xiaoli Chen, Deguang Wang

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Influence of Leadership on Human–Artificial Intelligence Collaboration by Rodrigo Zárate-Torres, C. Fabiola Rey-Sarmiento, Julio César Acosta-Prado, Nelson Alfonso Gómez-Cruz, Dorys Yaneth Rodríguez Castro, José Camargo

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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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Improving network security using keyboard dynamics: A comparative study by Ugwunna, C.O., Chukwuogo, O.E., Alabi, O.A., Kareem, M.K., Belonwu, T.S., Oloyede, S.O.

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Identification of cell adhesion-related subtypes and construction of risk model to predict breast cancer prognostic and immunological properties by De-Ming Lv, Li Yang, Chen Fan, Ling-Hui Fang, Su-Fen Cheng

“…Finally, potential drugs and drug sensitivity was evaluated using pRRobhetic algorithm. Results Based on the expression levels of 39 genes related to cell adhesion, we identified 3 distinct subtypes, and LASSO regression analysis identified 8 genes that could be used as prognostic markers. …”
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Optimising management against dynamic threats: A spatially explicit approach based on integer programming by José Salgado‐Rojas, Virgilio Hermoso, Eduardo Álvarez‐Miranda

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