Optimized Trust Prediction and Multi-Criteria Framework for Task and Data Collector Selection Using Deep Learning in Ubiquitous Environments by Ahmed A. A. Gad-Elrab

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A prospective cluster randomized trial of an interventions bundle to reduce inappropriate antibiotic use for upper respiratory tract infections in the outpatient setting by Adeel A. Butt, Sherin Shams, Atika Jabeen, Asma Ali Al-Nuaimi, Jeyaram Illiayaraja Krishnan, Aimon B. Malik, Samah Saleem, Maryam Hassan Abdulaziz, Naheel Ismail Seyam, Kamran Aziz, Dalia Kandil, Anil G. Thomas, Hanaa Nafady-Hego, Muzna I. Lone, Jameela Al Ajmi, Zain A. Bhutta, Noora AlSulaiti, Wael E. Said Hussein, Sandy Semaan, Samya Ahmad Al-Abdulla, Mohamed Ghaith Al-Kuwari, Abdul-Badi Abou-Samra

“…Intervention Bundled 4-component intervention including extensive provider education, a decision support algorithm, option for deferred antibiotics prescription, and monthly feedback on prescription patterns, vs. a single randomly assigned intervention (decision support algorithm). …”
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Crack Tracking in Small-Diameter Metal Pipe Using Controlled Motor Vibrations and Flexible Sensor by Md Rabiul Awal, Nurul Atiqah Tajulmar, Muhammad Syarifuddin Yahya, Nurafnida Afrizal, Wan Hafiza Wan Hassan, Nurul Adilah Abdul Latiff, Shakir Saat

“…However, it is very tricky in the case of a bent pipe, as the pressure differences are less than 300 a.u. for three conditions and above for only one. Hence, it might provoke an incorrect decision when detecting a bent pipe. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…Nine machine learning algorithms (Logistic Regression LR, Decision Tree DT, Gradient Boosting Machine GBM, K-Nearest Neighbors KNN, LASSO, Principal Component Analysis PCA, Random Forest RF, Support Vector Machine SVM, and XGBoost) were applied to training and testing datasets with 10-fold cross-validation to select three optimized algorithm models. …”
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Sleep Stage Classification using Laplacian Score Feature Selection Method by Single Channel EEG by Mahtab Vaezi, Mehdi Nasri

“…Simulation results confirms the superiority of the proposed method based on the classification results. With the proposed algorithm, 2, 3, 4, 5 and 6 stages of sleep were classified by SVM and decision tree with 98.0%, 98.0%, 97.3%, 96.6%, and 95.0% accuracy, which are more superior to previous methodâs results.…”
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Development of a machine learning-derived model to predict unplanned ICU admissions after major non-cardiac surgery by Catherine Chiu, Matthias R. Braehler, Anne L. Donovan, Atul J. Butte, Romain Pirracchio, Andrew M. Bishara

“…We developed our prediction model with a gradient-boosting decision tree algorithm (XGBoost). The model incorporated sixteen generalizable predictor variables that were derived from the demographics and surgical booking details. …”
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Agile DQN: adaptive deep recurrent attention reinforcement learning for autonomous UAV obstacle avoidance by Fadi AlMahamid, Katarina Grolinger

“…Abstract Unmanned Aerial Vehicle (UAV) obstacle avoidance in 3D environments demands sophisticated handling of high-dimensional inputs and effective state representations. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…To minimize overfitting in each algorithm, K-fold cross-validation methodology is employed during the training phase. …”
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Predicting 30-day in-hospital mortality in ICU asthma patients: a retrospective machine learning study with external validation by Yuanshuo Ge, Guangdong Wang, Tingting Liu, Wenwen Ji, Jiaolin Sun, Yaxin Zhang

“…Feature selection was conducted using both LASSO regression and the Boruta algorithm. Seven machine learning algorithms were trained and evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis. …”
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Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks by Kun Mei, Zikang Feng, Hui Liu, Min Wang, Chao Ce, Shi Yin, Xiaoying Zhang, Bin Wang

“…Feature selection was performed using the Lasso algorithm to identify the most predictive variables, which were subsequently incorporated into the radiomics-based neural network model. …”
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Convolution of the physical point cloud for predicting the self-assembly of colloidal particles by Seunghoon Kang, Young Jin Lee, Kyung Hyun Ahn

“…This paper presents a novel algorithm for predicting the kinetic and thermodynamic pathways of colloidal systems. …”
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The octoPus: An open-source software for supporting farmers in the control of grapevine downy mildew by Simone Bregaglio, Eleonora Del Cavallo, Lorenzo Ascari, Eugenio Rossi

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Passenger Demand-Oriented High-Speed Train Stop Planning with Service-Node Features Analysis by Fanxiao Liu, Qiyuan Peng, Gongyuan Lu, Guangyuan Zhang

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Clinic-morphological substantiation of the parahernial tissues excision in hernio-abdominoplasty in patients with ventral obesity by A. O. Kot

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Toward Trustworthy Machine Learning for Daily Sediment Modeling in the Riverine Systems: An Integrated Framework With Enhanced Uncertainty Quantification and Interpretability by Z. J. Yue, N. N. Wang, B. D. Xu, X. Huang, D. M. Yang, H. B. Xiao, Z. H. Shi

“…Based on 41‐year multi‐source data and three ensemble learning algorithms (LightGBM, XGBoost, and random forest (RF)), this study models daily suspended sediment concentration (SSC) separately for seven subtropical watersheds and evaluates overall and local accuracy. …”
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Research on optimization technology of new pipeline design for regional natural gas pipeline network by Jingyi CUI, Kunfeng ZHU, Cuixian GAO, Li GU, Jing REN, Yuxing LI, Wuchang WANG

“…Secondly, a particle swarm optimization algorithm was utilized for model solution optimization. …”
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China by Shaowu Lin, Sicheng Li, Ya Fang

“…Methods Ninety-two participants aged over 60 from Xiamen, China, were recruited for a three-week cross-sectional study. Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression Scale, with a score of ≥ 10 indicating depression. …”
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Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…The results of machine learning algorithms are demonstrated for sets of real statistical data representing the closing prices of shares of three Russian companies “Sberbank”, “Aeroflot”, “Gazprom” in the period from 01.12.2019 to 30.11.2020, obtained from the website of the Investment Company “FINAM”. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Furthermore, the Ordered Weighted Averaging (OWA) algorithm and the Partical Swarm Optimization-Support Vector Machine (PSO-SVM) model were combined to simulate future GDV scenarios for 2030–2050 under three development preferences: environment oriented, status quo, and economically oriented. …”
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Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches by Suleiman Ibrahim Mohammad, Hamza Abu Owida, Asokan Vasudevan, Suhas Ballal, Shaker Al-Hasnaawei, Subhashree Ray, Naveen Chandra Talniya, Aashna Sinha, Vatsal Jain, Ahmad Abumalek

“…The Coupled Simulated Annealing (CSA) algorithm was employed to optimize the hyperparameters of these models, enhancing their predictive performance. …”
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