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Nest site selection patterns of a local Egyptian VultureNeophron percnopteruspopulation in Turkey

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Economic and Biological Conditions Influence the Sustainability of Harvest of Wild Animals and Plants in Developing Countries

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Quincy: Detecting Host-Based Code Injection Attacks in Memory Dumps

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Subcategory-Aware Feature Selection and SVM Optimization for Automatic Aerial Image-Based Oil Spill Inspection

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Contributions of Actual and Simulated Satellite SAR Data for Substrate Type Differentiation and Shoreline Mapping in the Canadian Arctic

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Application of Random Forest, Rough Set Theory, Decision Tree and Neural Network to Detect Financial Statement Fraud – Taking Corporate Governance into Consideration

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Use of smartphone sensors to quantify the productive cycle elements of hand fallers on industrial cable logging operations

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Exploring the relative importance of biotic and abiotic factors that alter the self-thinning rule: Insights from individual-based modelling and machine-learning

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Identification of the Debris Flow Process Types within Catchments of Beijing Mountainous Area

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An Enhanced Random Forests Approach to Predict Heart Failure From Small Imbalanced Gene Expression Data

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Space-time modelling of groundwater level and salinity

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Random Forests based feature selection for decoding fMRI data

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Understanding the spatial non-stationarity in the relationships between malaria incidence and environmental risk factors using Geographically Weighted Random Forest: A case study in Rwanda.

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Prediction and Optimization of Process Parameters using Artificial Intelligence and Machine Learning Models

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A material stack-up combination identification method for resistance spot welding based on dynamic resistance

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Predicting Mental Health Treatment Access Among Adolescents With Elevated Depressive Symptoms: Machine Learning Approaches

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Predicting intraurban airborne PM1.0-trace elements in a port city: Land use regression by ordinary least squares and a machine learning algorithm

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Root cause analysis of industrial faults based on binary extreme gradient boosting and temporal causal discovery network

Qin, K., Chen, L., Shi, J., Li, Z., & Hao, K. (2022) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2022.104559 · Cited by 23

Magnetic resonance imaging parameter-based machine learning for prognosis prediction of high-intensity focused ultrasound ablation of uterine fibroids

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Thermomechanical fatigue behavior and lifetime modeling of powder metallurgy superalloy considering phase angle effect

Shen, J., Hu, X., Mi, D., Qian, Z., Teng, X., Song, X., Jiang, Y., & Nie, X. (2022) · International Journal of Fatigue · doi:10.1016/j.ijfatigue.2022.107164 · Cited by 22

Estimation of surface ozone concentration over Jiangsu province using a high-performance deep learning model

Mu, X., Wang, S., Jiang, P., & Wu, Y. (2022) · Journal of Environmental Sciences · doi:10.1016/j.jes.2022.09.032 · Cited by 22

Controlling factors in the variability of soil magnetic measures by machine learning and variable importance analysis

Azizi, K., Ayoubi, S., & Demattê, J. A. M. (2023) · Journal of Applied Geophysics · doi:10.1016/j.jappgeo.2023.104944 · Cited by 23

A survey on air pollutant PM2.5 prediction using random forest model

Babu, S., & Thomas, B. (2023) · Environmental Health Engineering and Management · doi:10.34172/ehem.2023.18 · Cited by 22

Relative impact of environmental variables on the lake trophic state highlights the complexity of eutrophication controls

Zawiska, I., Jasiewicz, J., Rzodkiewicz, M., & Woszczyk, M. (2023) · Journal of Environmental Management · doi:10.1016/j.jenvman.2023.118679 · Cited by 22

Caution is needed across Mediterranean ecosystems when interpreting wall-to-wall fire severity estimates based on spectral indices

Fernández‐Guisuraga, J. M., Fernandes, P. M., Marcos, E., Beltrán-Marcos, D., Sarricolea, P., Farris, M., & Calvo, L. (2023) · Forest Ecology and Management · doi:10.1016/j.foreco.2023.121383 · Cited by 22

Ebike Sharing vs. Bike Sharing: Demand Prediction Using Deep Neural Networks and Random Forests

Schnieder, M. (2023) · Sustainability · doi:10.3390/su151813898 · Cited by 22

Estimating the Quality of the Most Popular Machine Learning Algorithms for Landslide Susceptibility Mapping in 2018 Mw 7.5 Palu Earthquake

Ma, S., Shao, X., & Xu, C. B. (2023) · Remote Sensing · doi:10.3390/rs15194733 · Cited by 22

Optimal Support Vector Machines for forest above-ground biomass estimation from multisource remote sensing data

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Application of data mining methods for classification and prediction of olive oil blends with other vegetable oils

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A Methodology for Predictive Maintenance in Semiconductor Manufacturing

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Carapace asymmetry: A possible biomarker for metal accumulation in adult olive Ridleys marine turtles?

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Identification of Vehicle-Pedestrian Collision Hotspots at the Micro-Level Using Network Kernel Density Estimation and Random Forests: A Case Study in Shanghai, China

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Improving Diagnosis Efficiency via Machine Learning

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Prospective breast cancer risk factors prediction in Saudi women

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Action-based Recommendation in Pull-request Development

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Personalized Subjective Driving Risk: Analysis and Prediction

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A cross-linguistic analysis of the temporal dynamics of turn-taking cues using machine learning as a descriptive tool

Brusco, P., Vidal, J., Stefan Benus, A., & Gravano, A. (2020) · Speech Communication · doi:10.1016/j.specom.2020.09.004 · Cited by 22

Seasonality of agricultural exposure as an important predictor of seasonal yellow fever spillover in Brazil

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Joint learning of ultrasonic backscattering statistical physics and signal confidence primal for characterizing atherosclerotic plaques using intravascular ultrasound

Sheet, D., Karamalis, A., Eslami, A., Noël, P. B., Chatterjee, J., Ray, A. K., Laine, A. F., CARLIER, S. G., Navab, N., & Katouzian, A. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.10.002 · Cited by 24

Partial least squares-based human upper body orientation estimation with combined detection and tracking

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Multi-modal MRI classifiers identify excessive alcohol consumption and treatment effects in the brain

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Construction of Membership Functions for Soil Mapping using the Partial Dependence of Soil on Environmental Covariates Calculated by Random Forest

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Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction

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Maximizing Impacts of Remote Sensing Surveys in Slope Stability—A Novel Method to Incorporate Discontinuities into Machine Learning Landslide Prediction

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Recent advances in the prediction of thermophysical properties of nanofluids using artificial intelligence

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Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China

Zhao, B., Zhu, J., Hu, Y., Liu, Q., & Liu, Y. (2022) · Geofluids · doi:10.1155/2022/2058442 · Cited by 21

Consistent and unbiased variable selection under indepedent features using Random Forest permutation importance

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Creating a spatially continuous air temperature dataset for Taiwan using thermal remote-sensing data and machine learning algorithms

Tran, D.-P., & Liou, Y. (2023) · Ecological Indicators · doi:10.1016/j.ecolind.2023.111469 · Cited by 21

Predicting the suitable habitat distribution of berry plants under climate change

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Predicting the binding configuration and release potential of heavy metals on iron (oxyhydr)oxides: A machine learning study on EXAFS

Liu, J., Zhao, J., Du, J., Peng, S., Wu, J., Zhang, W., Xu, Y., & Lin, Z. (2024) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2024.133797 · Cited by 21

Influencing factors of spatial vitality in underground space around railway stations: A case study in Shanghai

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Using comparative extinction risk analysis to prioritize the IUCN Red List reassessments of amphibians

Lucas, P. M., Marco, M. D., Cazalis, V., Luedtke, J. A., Neam, K., Brown, M. H., Langhammer, P. F., Mancini, G., & Santini, L. (2024) · Conservation Biology · doi:10.1111/cobi.14316 · Cited by 22

Introducing new morphometric parameters to improve urban canopy air flow modeling: A CFD to machine-learning study in real urban environments

Wehrle, J., Jung, C., Giometto, M. G., Christen, A., & Schindler, D. (2024) · Urban Climate · doi:10.1016/j.uclim.2024.102173 · Cited by 21

Sectoral exposure of financial markets to oil risk factors in BRICS countries

Dogah, K. E., & Premaratne, G. (2018) · Energy Economics · doi:10.1016/j.eneco.2018.09.014 · Cited by 21

An Online Method Based on Random Forest for Air Pollutant Concentration Forecasting

Li, J., Shao, X., & Zhao, H. (2018) · Chinese Control Conference (CCC) · doi:10.23919/chicc.2018.8483621 · Cited by 21

Developing a Travel Time Estimation Method of Freeway Based on Floating Car Using Random Forests

Cheng, J., Li, G., & Chen, X. (2019) · Journal of Advanced Transportation · doi:10.1155/2019/8582761 · Cited by 21

Offline and Online Learning Techniques for Personalized Blood Pressure Prediction and Health Behavior Recommendations

Chiang, P.-H., & Dey, S. (2019) · IEEE Access · doi:10.1109/access.2019.2939218 · Cited by 23

Automatic diagnosis of valvular heart diseases by impedance cardiography signal processing

Salah, I. B., la Rosa, R. D., Ouni, K., & Salah, R. B. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.101758 · Cited by 21

Knowledge-driven decision analytics for commercial banking

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Quantile Regression Forests to Identify Determinants of Neighborhood Stroke Prevalence in 500 Cities in the USA: Implications for Neighborhoods with High Prevalence

Hu, L., Ji, J., Li, Y., Liu, B., & Zhang, Y. (2020) · Journal of Urban Health · doi:10.1007/s11524-020-00478-y · Cited by 21

Nonparametric feature selection by random forests and deep neural networks

Mao, X., Peng, L., & Wang, Z. (2022) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2022.107436 · Cited by 21

Determination of the influence factors on household vehicle ownership patterns in Phnom Penh using statistical and machine learning methods

Ha, T. V., ASADA, T., & Arimura, M. (2019) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2019.05.015 · Cited by 21

Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters

Zewdie, G. K., Liu, X., Wu, D., Lary, D. J., & Levetin, E. (2019) · Environmental Monitoring and Assessment · doi:10.1007/s10661-019-7428-x · Cited by 21

Assessing temporal and spatial variation in sensitivity of communities of periphyton sampled from agroecosystem to, and ability to recover from, atrazine exposure

Prosser, R. S., Brain, R. A., Andrus, J. M., Hosmer, A. J., Solomon, K. R., & Hanson, M. L. (2015) · Ecotoxicology and Environmental Safety · doi:10.1016/j.ecoenv.2015.04.047 · Cited by 21

Analysing flood fatalities in Vietnam using national disaster database and tree-based methodsPreprint

Luu, C., von Meding, J. K., & Kanjanabootra, S. (2017) · doi:10.5194/nhess-2017-155 · Cited by 21

Machine learning based on functional principal component analysis to quantify the effects of the main drivers of wheat yields

Bonneu, F., Makowski, D., Joly, J., & Allard, D. (2024) · European Journal of Agronomy · doi:10.1016/j.eja.2024.127254 · Cited by 20

A Method for Predicting Indoor CO2 Concentration in University Classrooms: An RF-TPE-LSTM Approach

Dai, Z., Yuan, Y., Zhu, X., & Zhao, L. (2024) · Applied Sciences · doi:10.3390/app14146188 · Cited by 20

Integrated Remote Sensing and Deep Learning Models for Flash Flood Detection Based on Spatio-temporal Land Use and Cover Changes in the Mediterranean Region

Hasnaoui, Y., Tachi, S. E., Bouguerra, H., Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Z. M., Gilja, G., Szczepanek, R., & Navarro-Pedreño, J. (2025) · Environmental Modeling & Assessment · doi:10.1007/s10666-025-10035-z · Cited by 20

What can artificial intelligence do for soil health in agriculture?

Schweng, S., Bernardini, L. G., Keiblinger, K. M., Kaul, H., Fister, I., Lukač, N., Ser, J. D., & Holzinger, A. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100832 · Cited by 22

A physiology-based mathematical model for the selection of appropriate ventilator controls for lung and diaphragm protection

Zhang, B., Ratano, D., Brochard, L. J., Georgopoulos, D., Duffin, J., Long, M., Schepens, T., Telías, I., Slutsky, A. S., Goligher, E. C., et al. (2020) · Journal of Clinical Monitoring and Computing · doi:10.1007/s10877-020-00479-x · Cited by 20

Identification of Potential Biomarkers for Anti-PD-1 Therapy in Melanoma by Weighted Correlation Network Analysis

Wang, X., Chai, Z., Li, Y., Long, F., Hao, Y., Pan, G., Liu, M., & Li, B. (2020) · Genes · doi:10.3390/genes11040435 · Cited by 20

Development and validation of smartwatch-based activity recognition models for rigging crew workers on cable logging operations

Zimbelman, E. G., & Keefe, R. F. (2021) · PLoS ONE · doi:10.1371/journal.pone.0250624 · Cited by 21

Using Machine Learning and Wearable Inertial Sensor Data for the Classification of Fractal Gait Patterns in Women and Men During Load Carriage

Ahamed, N. U., Krajewski, K. T., Johnson, C. C., Sterczala, A. J., Greeves, J. P., Wardle, S. L., O’Leary, T. J., Mi, Q., Flanagan, S. D., Nindl, B. C., et al. (2021) · Procedia Computer Science · doi:10.1016/j.procs.2021.05.030 · Cited by 20

Lipid level alteration in human and cellular models of alpha synuclein mutations

Avisar, H., Guardia‐Laguarta, C., Surface, M., Papagiannakis, N., Maniati, M., Antonelou, R. C., Papadimitriou, D. A., Koros, C., Athanassiadou, A., Przedborski, S., et al. (2022) · npj Parkinson s Disease · doi:10.1038/s41531-022-00313-y · Cited by 20

A comprehensive study on the performance of different Multi-class Classification Algorithms and Hyperparameter Tuning Techniques using Optuna

Joy, J., & Selvan, M. P. (2022) · International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS) · doi:10.1109/ic3sis54991.2022.9885695 · Cited by 20

Prediction of forest nutrient and moisture regimes from understory vegetation with random forest classification models

Lisein, J., Fayolle, A., Andyne, L., Prevot, C., & Hugues, C. (2022) · Ecological Indicators · doi:10.1016/j.ecolind.2022.109446 · Cited by 20

Interannual variation and machine learning simulation of organophosphate esters in Taihu Lake

Zhang, Y., Cheng, X., Chen, X., Ding, L., Xiao, H., Liu, K., Yang, S., Li, H., & He, H. (2023) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2023.132654 · Cited by 20

Study on fault identification rules for real refrigerant leakage in R290 room air conditioner based random forest algorithm

Yang, J., Wu, J., Yu, X., & Liang, Y. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122126 · Cited by 20

Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree

Teodoro, G. D., Monaci, M., & Palagi, L. (2024) · EURO Journal on Computational Optimization · doi:10.1016/j.ejco.2024.100084 · Cited by 20

Optimizing variables selection of random forest to predict radial growth of Larix gmelinii var. principis-rupprechtii in temperate regions

Zhang, Y., Liao, J., Du, M., Du, M., & Zhang, X. (2024) · Forest Ecology and Management · doi:10.1016/j.foreco.2024.122159 · Cited by 20

Enhancing photovoltaic performance in tin-based perovskite solar cells: A unified approach utilizing numerical simulation and machine learning techniques

Subudhi, P., Shoba, S., Rahul Narasimhan, A., Kumar, B., & Punetha, D. (2025) · Journal of Power Sources · doi:10.1016/j.jpowsour.2025.236639 · Cited by 20

Automatic fusion and classification of hyperspectral and LiDAR data using random forests

Merentitis, A., Debes, C., Heremans, R., & Frangiadakis, N. (2014) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2014.6946658 · Cited by 20

Splice site identification in human genome using random forest

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The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success

Lehrer, S., & Xie, T. (2021) · Management Science · doi:10.1287/mnsc.2020.3911 · Cited by 21

An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

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Quantifying coconut palm extent on Pacific islands using spectral and textural analysis of very high resolution imagery

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An Evaluation of Machine Learning Algorithms To Detect Attacks in Scada Network

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Remote Sensing of Lake Sediment Core Particle Size Using Hyperspectral Image Analysis

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Data analytics and clinical feature ranking of medical records of patients with sepsis

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