Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors by Michael Reich, Njira Lugogo, Laurie D Snyder, Megan L Neely, Guilherme Safioti, Randall Brown, Michael DePietro, Roy Pleasants, Thomas Li, Lena Granovsky

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Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System by Hussein Ali Salah, Ahmed Shihab Ahmed

“…In this paper, it was suggested the use of C4.5 Algorithm for decision tree.…”
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Theoretical knowledge enhanced genetic algorithm for mine ventilation system optimization considering main fan adjustment by Wentian Shang, Jinzhang Jia

“…Comparative analysis with four other algorithms shows that, although this algorithm has a longer runtime due to the need to identify the minimum spanning tree during iterations, its ability to reduce problem dimensionality and improve population quality results in more stable and superior convergence performance, especially for large-scale mine ventilation systems. …”
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Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) by Min Tan, Jinjin Zhao, Yushun Tao, Uroosa Sehar, Yan Yan, Qian Zou, Qing Liu, Long Xu, Zeyang Xia, Lijuan Feng, Jing Xiong

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Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms by Anjan Kumar Pradhan, Prasad Gandham, Kanniah Rajasekaran, Niranjan Baisakh

“…Improved performances of the algorithms via feature selection from the raw gene features identified 235 unique genes as top candidate genes across all models for all stresses. …”
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Comparative Analysis of Machine Learning Algorithms for Predicting Patient Admission in Emergency Departments Using EHR Data by Ahmad Abdul Chamid, Ratih Nindyasari, Muhammad Imam Ghozali

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Predicting Irrigation Water Quality Indices Based on Data-Driven Algorithms: Case Study in Semiarid Environment by Dimple Dimple, Jitendra Rajput, Nadhir Al-Ansari, Ahmed Elbeltagi

“…The SVM model showed the best-fit model for all irrigation indices during testing, that is, RMSE: 0.0662, 4.0568, 3.0168, 0.1113, 3.7046, and 5.1066; r: 0.9364, 0.9618, 0.9588, 0.9819, 0.9547, and 0.8903; MSE: 0.004381, 16.45781, 9.101218, 0.012383, 13.72447, and 26.078; MAE: 0.042, 3.1999, 2.3584, 0.0726, 2.9603, and 4.0582 for KR, MH, SSP, SAR, %Na, and PI, respectively. …”
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Identifying determinants of malnutrition in under-five children in Bangladesh: insights from the BDHS-2022 cross-sectional study by Tanzila Tamanna, Shohel Mahmud, Nahid Salma, Md. Musharraf Hossain, Md. Rezaul Karim

“…Descriptive statistics were conducted to summarize the key characteristics of the dataset. Boruta algorithm was employed to identify important features related to malnutrition which were then used to evaluate several machine learning models, including K-Nearest Neighbors (KNN), Neural Networks (NN), Classification and Regression Trees (CART), XGBoost (XGBM), Support Vector Machines (SVM), and Random Forest (RF), in addition to the traditional logistic regression (LR) model. …”
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The application of a recommendation algorithm to the selection of places and the volume of planting of forest plantations, taking into account various characteristics by Korzhova Maria, Andreeva Kristina, Zolotarev Daniil, Zolnikov Vladimir

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Modeling habitat suitability for endangered herb (Salvia leriifolia Benth) using Innovative hybrid machine learning algorithms by Emran Dastres, Hamidreza Rabiei-Dastjerdi, Hassan Esmaeili, Mahdis Amiri, Ali Sonboli, Mohammad Hossein Mirjalili

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An Image-Based Concrete-Crack-Width Measurement Method Using Skeleton Pruning and the Edge-OrthoBoundary Algorithm by Chunxiao Li, Hui Qin, Yu Tang, Hailiang Zhao, Shengshen Pan, Jinbo Liu, Wenjiang Luo

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The Impact of Image Spatial Resolution and Machine Learning Algorithm on Urban Vegetation Classification: Focus on Data Loss and Misclassification by Alexander Takele Muleta, Julius Bamah, Shirley Bushner, Oz Kira

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Advancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges by Shunlin Liang, Tao He, Jianxi Huang, Aolin Jia, Yuzhen Zhang, Yunfeng Cao, Xiaona Chen, Xidong Chen, Jie Cheng, Bo Jiang, Huaan Jin, Ainong Li, Siwei Li, Xuecao Li, Liangyun Liu, Xiaobang Liu, Han Ma, Yichuan Ma, Dan-Xia Song, Lin Sun, Yunjun Yao, Wenping Yuan, Guodong Zhang, Yufang Zhang, Liulin Song

“…The majority of this paper reviews the inversion algorithms and existing regional to global products of 18 variables in four major categories: 1) Land surface radiation, including broadband albedo, land surface temperature, and all-wave net radiation; 2) Terrestrial ecosystem variables, including leaf area index, fraction of absorbed photosynthetically active radiation, fractional vegetation cover, fractional forest cover, tree height, forest above-ground biomass gross primary production, net primary production, and agricultural crop yield; 3) Water cycle and cryosphere, including soil moisture, evapotranspiration, and snow cover; and 4) Land surface types, such as global land cover, impervious surface, inland water, crop type, and fire. …”
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Development and Validation of a Machine Learning Model for Early Prediction of Sepsis Onset in Hospital Inpatients from All Departments by Pierre-Elliott Thiboud, Quentin François, Cécile Faure, Gilles Chaufferin, Barthélémy Arribe, Nicolas Ettahar

“…The binary classifier SEPSI Score for sepsis prediction was constructed using a gradient boosted trees approach, and assessed on the study dataset of 5270 patient stays, including 121 sepsis cases (2.3%). …”
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Mapping previously undetected trees reveals overlooked changes in pan-tropical tree cover by Shidong Liu, Jie Zhang, Li Wang, Philippe Ciais, Jianjun Zhang, Josep Penuelas, Biswajit Nath, Iskid Jacquet, Xia Wu, Shengping Ding, Wang Li, Ni Huang, Wanjuan Song, WenJian Ni, Zheng Niu

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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Outcomes were synthesised narratively. Two decision trees were used for cost-effectiveness: (1) a simple decision tree for the detection of actionable nodules and (2) a decision tree reflecting the full clinical pathways for people undergoing chest computed tomography scans. …”
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Domain adaptation of deep neural networks for tree part segmentation using synthetic forest trees by Mitch Bryson, Ahalya Ravendran, Celine Mercier, Tancred Frickey, Sadeepa Jayathunga, Grant Pearse, Robin J.L. Hartley

“…Supervised deep learning algorithms have recently achieved state-of-the-art performance in the classification, segmentation and analysis of 3D LiDAR point cloud data in a wide-range of applications and environments. …”
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Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine by Hojin Moon, Lauren Tran, Andrew Lee, Taeksoo Kwon, Minho Lee

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Efficient Path Planning in Multi-Agent Environment of AAVs With Payloads by Annapurna Jonnalagadda, Yuva Sai Verma, M. V. Bharat, E. Z. Ushus

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