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Development and Utilization of Bridge Data of the United States for Predicting Deck Condition Rating Using Random Forest, XGBoost, and Artificial Neural Network

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Predictive modeling for the adsorptive and photocatalytic removal of phenolic contaminants from water using artificial neural networks

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Detecting new obfuscated malware variants: A lightweight and interpretable machine learning approach

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Distribution of individual members of the mosquito Anopheles maculipennis complex in G ermany identified by newly developed real‐time PCR assays

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An infrared spectroscopic blood test for non-small cell lung carcinoma and subtyping into pulmonary squamous cell carcinoma or adenocarcinoma

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Stock market trend prediction using AHP and weighted kernel LS-SVM

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Detection of phishing websites using a novel twofold ensemble model

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Importance of Ecological Variables in Explaining Population Dynamics of Three Important Pine Pest Insects

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Modeling wetland aboveground biomass in the Poyang Lake National Nature Reserve using machine learning algorithms and Landsat-8 imagery

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Retrieval of the Soil Salinity From Sentinel-1 Dual-Polarized SAR Data Based on Deep Neural Network Regression

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Nondestructive freshness evaluation of intact prawns (Fenneropenaeus chinensis) using line-scan spatially offset Raman spectroscopy

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RF‐LSTM‐based method for prediction and diagnosis of fouling in heat exchanger

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Mapping coastal wetlands in the Yellow River Delta, China during 2008–2019: impacts of valid observations, harmonic regression, and critical months

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Vertical patterns and controlling factors of soil nitrogen in deep profiles on the Loess Plateau of China

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Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV–LiDAR and Machine Learning Methods

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Application of Boruta algorithms as a robust methodology for performance evaluation of CMIP6 general circulation models for hydro-climatic studies

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Using Boruta-Selected Spectroscopic Wavebands for the Asymptomatic Detection of Fusarium Circinatum Stress

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Prevalence and predictors of posttraumatic stress disorder and depressive symptoms among burn survivors two years after the 2015 Formosa Fun Coast Water Park explosion in Taiwan

Su, Y. (2018) · European Journal of Psychotraumatology · doi:10.1080/20008198.2018.1512263 · Cited by 33

Naturalized distributions show that climatic disequilibrium is structured by niche size in pines (PinusL.)

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Multi-scenario prediction and path optimization of industrial carbon unlocking in China

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Intelligent green retrofitting of existing buildings based on case-based reasoning and random forest

Liu, T., Ma, G., Wang, D., & Pan, X. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105377 · Cited by 31

Examining the Spectral Separability of Prosopis glandulosa from Co-Existent Species Using Field Spectral Measurement and Guided Regularized Random Forest

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Perceptions of climate change across the Canadian forest sector: The key factors of institutional and geographical environment

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Does governance efficiency matter for national innovative capacity? One tale from different countries

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Determinants of dining satisfaction

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Applying a data-driven approach to quantify EEG maturational deviations in preterms with normal and abnormal neurodevelopmental outcomes

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A Data‐Driven Framework to Characterize State‐Level Water Use in the United States

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Feature selection for predicting tool wear of machine tools

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Predicting outcomes in older ED patients with influenza in real time using a big data-driven and machine learning approach to the hospital information system

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Development of a tRNA-derived small RNA diagnostic and prognostic signature in liver cancer

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Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma

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An integrated model for crude oil forecasting: Causality assessment and technical efficiency

Cheng, X. Y., Wu, P. C., Liao, S. S., & Wang, X. (2022) · Energy Economics · doi:10.1016/j.eneco.2022.106467 · Cited by 31

Delineation of Orchard, Vineyard, and Olive Trees Based on Phenology Metrics Derived from Time Series of Sentinel-2

Abubakar, M., Chanzy, A., Flamain, F., Pouget, G., & Courault, D. (2023) · Remote Sensing · doi:10.3390/rs15092420 · Cited by 31

Range-wide differential adaptation and genomic offset in critically endangered Asian rosewoods

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The use of machine learning techniques for assessing the potential of organizational resilience

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The Effects of Improved Water Quality on Fish Assemblages in a Heavily Modified Large River System

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A data driven model for optimal orthosis selection in children with cerebral palsy

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Estimating residual variance in random forest regression

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BREAST CANCER ANALYSIS USING LOGISTIC REGRESSION

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Autoregressive Planet Search: Methodology

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DNN-DP: Differential Privacy Enabled Deep Neural Network Learning Framework for Sensitive Crowdsourcing Data

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Monitoring and assessment of spatiotemporal soil salinization in the Lake Urmia region

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Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks

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The Sound of Rebellion: Voting Dissent and Legislative Speech in the UK House of Commons

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Seepage and dam deformation analyses with statistical models: support vector regression machine and random forest

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Spatiotemporally Varying Coefficients (STVC) model: a Bayesian local regression to detect spatial and temporal nonstationarity in variables relationships

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C-band synthetic aperture radar (SAR) imagery for the classification of diverse cropping systems

Robertson, L. D., Davidson, A., McNairn, H. E., Hosseini, M., Mitchell, S. W., de Abelleyra, D., Verón, S. R., Maire, G. L., Plannells, M., Valero, S., et al. (2020) · International Journal of Remote Sensing · doi:10.1080/01431161.2020.1805136 · Cited by 30

Infestation risk of the intermediate snail host of Schistosoma japonicum in the Yangtze River Basin: improved results by spatial reassessment and a random forest approach

Zheng, J., Xia, S., Lv, S., Zhang, Y., Bergquist, R. N., & Zhou, X. (2021) · Infectious Diseases of Poverty · doi:10.1186/s40249-021-00852-1 · Cited by 30

Strong floristic distinctiveness across Neotropical successional forests

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Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland

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INTERACTIVE CADASTRAL BOUNDARY DELINEATION FROM UAV DATA

Crommelinck, S., Höfle, B., Koeva, M., Yang, M. Y., & George Vosselman, A. (2018) · ISPRS annals of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-annals-iv-2-81-2018 · Cited by 30

Cortico-Subthalamic Field Potentials Support Classification of the Natural Gait Cycle in Parkinson’s Disease and Reveal Individualized Spectral Signatures

Louie, K. H., Gilron, R., Yaroshinsky, M. S., Morrison, M. A., Choi, J. T., de Hemptinne, C., Little, S. J., Starr, P. A., & Wang, D. D. (2022) · eNeuro · doi:10.1523/eneuro.0325-22.2022 · Cited by 29

Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution

Chatzidiakou, L., Krause, A., Kellaway, M., Han, Y., Li, Y., Martin, E., Kelly, F. J., Zhu, T., Barratt, B., & Jones, R. L. (2022) · Environmental Health · doi:10.1186/s12940-022-00939-8 · Cited by 29

Local ecological knowledge and perception as a strategy in the management of ecosystem services

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Design and evaluation of features and classifiers for OLED panel defect recognition in machine vision

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Habitat diversity and structure regulate British bird richness: Implications of non-linear relationships for conservation

Carrasco, L., Norton, L., Henrys, P. A., SIRIWARDENA, G. M., Rhodes, C. J., Rowland, C. S., & Morton, D. (2018) · Biological Conservation · doi:10.1016/j.biocon.2018.08.010 · Cited by 29

Valuation of University-Originated Technologies: A Predictive Analytics Approach

Kim, Y., Ahn, J. M., Kwon, O.-J., & Lee, C. (2019) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2019.2938182 · Cited by 29

Winter Wheat Mapping Based on Sentinel-2 Data in Heterogeneous Planting Conditions

Zhang, D., Fang, S., She, B., Zhang, H., Ning, J., Xia, H., Yang, Y., & Ding, Y. (2019) · Remote Sensing · doi:10.3390/rs11222647 · Cited by 29

Short-Term Metro Passenger Flow Prediction Based on Random Forest and LSTM

Lin, S., & Tian, H. (2020) · IEEE Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) · doi:10.1109/itnec48623.2020.9084974 · Cited by 29

Factors associated with elevated levels of antibiotic resistance genes in sewer sediments and wastewater

Eramo, A., Medina, W. R. M., & Fahrenfeld, N. L. (2020) · Environmental Science Water Research & Technology · doi:10.1039/d0ew00230e · Cited by 29

Understanding Violin Players’ Skill Level Based on Motion Capture: a Data-Driven Perspective

D’Amato, V., Volta, E., Oneto, L., Volpe, G., Camurri, A., & Anguita, D. (2020) · Cognitive Computation · doi:10.1007/s12559-020-09768-8 · Cited by 31

Open Data and Machine Learning to Model the Occurrence of Fire in the Ecoregion of “Llanos Colombo–Venezolanos”

Barreto, J. S., & Armenteras, D. (2020) · Remote Sensing · doi:10.3390/rs12233921 · Cited by 29

Risk Factors Identification and Prediction of Anemia among Women in Bangladesh using Machine Learning Techniques

Islam, M. M., Rahman, M. J., Roy, D. C., Islam, M. M., Tawabunnahar, M., Ahmed, N. A. M. F., & Maniruzzaman, M. (2021) · Current Women s Health Reviews · doi:10.2174/1573404817666210215161108 · Cited by 29

Anthropogenic impacts on multiple facets of macroinvertebrate α and β diversity in a large river-floodplain ecosystem

Li, Z., García‐Girón, J., Zhang, J., Jia, Y., Jiang, X., & Xie, Z. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.162387 · Cited by 29

Which cropping systems to reconcile weed-related biodiversity and crop production in arable crops? An approach with simulation-based indicators

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Analysis and Comparison of Vector Space and Metric Space Representations in QSAR Modeling

Kausar, S., & Falcão, A. O. (2019) · Molecules · doi:10.3390/molecules24091698 · Cited by 29

A Predictive Model for Survival of Escherichia coli O157:H7 and Generic E. coli in Soil Amended with Untreated Animal Manure

Pang, H., Mokhtari, A. M., Chen, Y., Oryang, D., Ingram, D. T., Sharma, M., Millner, P. D., & Doren, J. M. V. (2020) · Risk Analysis · doi:10.1111/risa.13491 · Cited by 29

Feature Selection based on Information Theory

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Construction of multidimensional features to identify tea plantations using multisource remote sensing data: A case study of Hangzhou city, China

Kang, Y., Chen, Z., Li, L., & Zhang, Q. (2023) · Ecological Informatics · doi:10.1016/j.ecoinf.2023.102185 · Cited by 28

Climate factors drive plant distributions at higher taxonomic scales and larger spatial scales

Huang, E., Chen, Y., & Yu, S. (2024) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2023.1233936 · Cited by 28

Mineralocorticoid Receptor Antagonism Prevents Aortic Plaque Progression and Reduces Left Ventricular Mass and Fibrosis in Patients With Type 2 Diabetes and Chronic Kidney Disease: The MAGMA Trial

Rajagopalan, S., Dobre, M. A., Dazard, J.-E., Vergara-Martel, A., Connelly, K. A., Farkouh, M. E., Gaztañaga, J., Conger, H., Dever, A. M., Razavi-Nematollahi, L., et al. (2024) · Circulation · doi:10.1161/circulationaha.123.067620 · Cited by 29

A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques

Baruah, A., Bousiotis, D., Damayanti, S., Bigi, A., Ghermandi, G., Ghaffarpasand, O., Harrison, R. M., & Pope, F. D. (2024) · npj Climate and Atmospheric Science · doi:10.1038/s41612-024-00859-z · Cited by 28

Aboveground biomass estimation using multimodal remote sensing observations and machine learning in mixed temperate forest

Lamahewage, S. H. G., Witharana, C., Riemann, R. I., Fahey, R. T., & Worthley, T. E. (2025) · Scientific Reports · doi:10.1038/s41598-025-15585-6 · Cited by 28

Intelligent Sensing: The Emerging Integration of Machine Learning and Soft Sensors Based on Hydrogels and Ionogels

He, W., Lin, R., Kong, S., Qiang, M., Huang, L., Dai, B., Yao, X., Su, L., & Zhang, X. (2025) · Advanced Science · doi:10.1002/advs.202517851 · Cited by 28

Mining potential biomarkers associated with space flight in Caenorhabditis elegans experienced Shenzhou-8 mission with multiple feature selection techniques

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Environmental and Anthropogenic Factors Driving Changes in Paddy Soil Organic Matter: A Case Study in the Middle and Lower Yangtze River Plain of China

Naijia, G., Shi, X., Zhao, Y., Xu, S., Wang, M., Zhang, G., Wu, J., Huang, B., & Chao, K. O. N. G. (2017) · Pedosphere · doi:10.1016/s1002-0160(17)60383-7 · Cited by 28

CMEP: a database for circulating microRNA expression profiling

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Mapping Tasmania's cultural landscapes: Using habitat suitability modelling of archaeological sites as a landscape history tool

Jones, P., Williamson, G. J., Bowman, D. M. J. S., & Lefroy, E. C. (2019) · Journal of Biogeography · doi:10.1111/jbi.13684 · Cited by 28

Determining hypertensive patients’ beliefs towards medication and associations with medication adherence using machine learning methods

Aziz, F., Malek, S., Ali, A. M., Wong, M., Mosleh, M. A. A., & Milow, P. (2020) · PeerJ · doi:10.7717/peerj.8286 · Cited by 28

Investigation on the Alteration of Brain Functional Network and Its Role in the Identification of Mild Cognitive Impairment

Zhang, L., Ni, H., Yu, Z., Wang, J., Qin, J., Hou, F., Yang, A. C., & Initiative, A. D. N. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.558434 · Cited by 28

Utilizing world urban database and access portal tools (WUDAPT) and machine learning to facilitate spatial estimation of heatwave patterns

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