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Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson’s disease

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Assessing the Validity of k-Fold Cross-Validation for Model Selection: Evidence from Bankruptcy Prediction Using Random Forest and XGBoost

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A novel method for petroleum and natural gas resource potential evaluation and prediction by support vector machines (SVM)

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Assessing water quality of an ecologically critical urban canal incorporating machine learning approaches

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Aberrant Dynamic Functional Connectivity of Default Mode Network in Schizophrenia and Links to Symptom Severity

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Improving Sentiment Analysis of Arabic Tweets by One-way ANOVA

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Internet of medical things and trending converged technologies: A comprehensive review on real-time applications

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Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy

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Machine learning-driven prediction of phosphorus removal performance of metal-modified biochar and optimization of preparation processes considering water quality management objectives

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Intraoperative neural signals predict rapid antidepressant effects of deep brain stimulation

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Top ten intelligent algorithms towards smart manufacturing

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Using machine learning and an electronic tongue for discriminating saliva samples from oral cavity cancer patients and healthy individuals

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Machine learning with monotonic constraint for geotechnical engineering applications: an example of slope stability prediction

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Robust Arrhythmia Classification Based on QRS Detection and a Compact 1D-CNN for Wearable ECG Devices

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Deep Neural Generative Model of Functional MRI Images for Psychiatric Disorder Diagnosis

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A parallel strategy for predicting the quality of welded joints in automotive bodies based on machine learning

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A systematic review and methodological analysis of EEG-based biomarkers of Alzheimer's disease

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Video-based automatic lameness detection of dairy cows using pose estimation and multiple locomotion traits

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Machine learning unveils composition-property relationships in chalcogenide glasses

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Integrating an LSTM framework for predicting ankle joint biomechanics during gait using inertial sensors

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Machine Learning-Based Radio Coverage Prediction in Urban Environments

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Using machine learning to predict dimensions and qualify diverse part designs across multiple additive machines and materials

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A machine learning approach to the development and prospective evaluation of a pediatric lung sound classification model

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Towards wearable thermal comfort assessment framework by analysis of heart rate variability

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Embodied greenhouse gas emissions of buildings—Machine learning approach for early stage prediction

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LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds

Shaikh, F., Tai, H. K., Desai, N., & Siu, S. W. I. (2021) · Journal of Cheminformatics · doi:10.1186/s13321-021-00523-1 · Cited by 40

A Machine Learning-Driven Virtual Biopsy System For Kidney Transplant Patients

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Do machine learning methods improve prediction of ambient air pollutants with high spatial contrast? A systematic review

Vachon, J., Kerckhoffs, J., Buteau, S., & Smargiassi, A. (2024) · Environmental Research · doi:10.1016/j.envres.2024.119751 · Cited by 37

The structural similarity index for IMRT quality assurance: radiomics‐based error classification

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Associations between the urban exposome and type 2 diabetes: Results from penalised regression by least absolute shrinkage and selection operator and random forest models

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A classification algorithm of an SSVEP brain-Computer interface based on CCA fusion wavelet coefficients

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Machine Learning‐Assisted Prediction and Generation of Antimicrobial Peptides

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Investigation of Brain Functional Networks in Children Suffering from Attention Deficit Hyperactivity Disorder

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Improving spatial transferability of deep learning models for small-field crop yield prediction

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A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients

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CHOGlycoNET: Comprehensive glycosylation reaction network for CHO cells

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Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data

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Designing unique and high-performance Al alloys via machine learning: Mitigating data bias through active learning

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A Hybrid Capsule Network for Hyperspectral Image Classification

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Intrusive and non-intrusive early warning systems for thermal discomfort by analysis of body surface temperature

Wang, Z., Matsuhashi, R., & Onodera, H. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.120283 · Cited by 26

An intelligent based prediction of microbial behaviour in beef

Yücel, Ö., & Tarlak, F. (2023) · Food Control · doi:10.1016/j.foodcont.2023.109665 · Cited by 27

Automatic classification of infant vocalization sequences with convolutional neural networks

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The influence of HLA genotype on the development of metal hypersensitivity following joint replacement

Langton, D., Bhalekar, R. M., Joyce, T. J., Rushton, S. P., Wainwright, B. J., Nargol, M. E., Shyam, N., Lie, B. A., Pabbruwe, M. B., Stewart, A. J., et al. (2022) · Communications Medicine · doi:10.1038/s43856-022-00137-0 · Cited by 25

Applying a transformer architecture to intraoperative temporal dynamics improves the prediction of postoperative delirium

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Towards a novel method for detecting atypical lying down and standing up behaviors in dairy cows using accelerometers and machine learning

Brouwers, S., Simmler, M., Savary, P., & Scriba, M. F. (2023) · Smart Agricultural Technology · doi:10.1016/j.atech.2023.100199 · Cited by 23

Machine learning-based prediction of desalination capacity of electrochemical performance of nitrogen-doped for capacitive deionization

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Machine learning-assisted design of high-performance perovskite photodetectors: a review

Li, X. F., Mai, Y., Lan, C., Yang, F., Zhang, P., & Li, S. (2024) · Advanced Composites and Hybrid Materials · doi:10.1007/s42114-024-01113-z · Cited by 25

Voxel‐wise supervised analysis of tumors with multimodal engineered features to highlight interpretable biological patterns

Escobar, T., Vauclin, S., Orlhac, F., Nioche, C., Pineau, P., Champion, L., Brisse, H. J., & Buvat, I. (2022) · Medical Physics · doi:10.1002/mp.15603 · Cited by 22

A generalizable and interpretable model for mortality risk stratification of sepsis patients in intensive care unit

Zhuang, J., Huang, H., Jiang, S., Liang, J., Liu, Y., & Yu, X. (2023) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-023-02279-0 · Cited by 24

Study on the flexural performance and brittle fracture characteristics of steel fiber-reinforced concrete exposed to cryogenic temperatures

Liu, J., Cheng, L., & Zhou, D. (2024) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2024.136604 · Cited by 23

Multiple-Kernel Support Vector Machine for Predicting Internet Gaming Disorder Using Multimodal Fusion of PET, EEG, and Clinical Features

Jeong, B., Lee, J., Kim, H., Gwak, S., Kim, Y. K., Yoo, S. Y., Lee, D., & Choi, J. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.856510 · Cited by 21

Reservoir Computing for Early Stage Alzheimer’s Disease Detection

Mwamsojo, N., Lehmann, F., El‐Yacoubi, M. A., Merghem, K., Frignac, Y., Benkelfat, B.-E., & Rigaud, A. (2022) · IEEE Access · doi:10.1109/access.2022.3180045 · Cited by 23

Alterations in gut microbiota and host transcriptome of patients with coronary artery disease

Chen, L., Mou, X., Li, J., Li, M., Ye, C., Gao, X., Liu, X., Ma, Y., Xu, Y., & Zhong, Y. (2023) · BMC Microbiology · doi:10.1186/s12866-023-03071-w · Cited by 21

Optimized machine learning models for prediction of effective stiffness of rectangular reinforced concrete column sections

Sapkota, S. C., Das, S., & Saha, P. (2024) · Structures · doi:10.1016/j.istruc.2024.106155 · Cited by 20

Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence

Timilsina, M. S., Chaudhary, Y., Bhattarai, P., Uprety, B., & Khatiwada, D. (2024) · Energy Conversion and Management X · doi:10.1016/j.ecmx.2024.100783 · Cited by 24

Cross-Validation

Berrar, D. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-95502-7.00032-4 · Cited by 20

Machine learning-driven prediction of nitrate-N adsorption efficiency by Fe-modified biochar: Refined model tuning and identification of crucial features

Li, C., Xie, G., Li, J., Chen, X., Ma, H., & Wang, B. (2025) · Journal of Water Process Engineering · doi:10.1016/j.jwpe.2025.107026 · Cited by 19

An explainable boosting-based ensemble machine learning model for predicting the properties of date palm fiber reinforced concrete

Adamu, M., Sapkota, S. C., Das, S., Saha, P., & Ibrahim, Y. E. (2025) · Sustainable Chemistry and Pharmacy · doi:10.1016/j.scp.2025.101949 · Cited by 19

Statistical methods for validation of predictive models

Diniz, M. A. (2022) · Journal of Nuclear Cardiology · doi:10.1007/s12350-022-02994-7 · Cited by 22

A multi-channel UNet framework based on SNMF-DCNN for robust heart-lung-sound separation

Wang, W., Qin, D., Wang, S., Yu, F., & Zheng, Y. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107282 · Cited by 19

Resting-State Electroencephalogram Depression Diagnosis Based on Traditional Machine Learning and Deep Learning: A Comparative Analysis

Lin, H., Fang, J. S., Zhang, J., Zhang, X., Piao, W., & Liu, Y. (2024) · Sensors · doi:10.3390/s24216815 · Cited by 20

Practical guidelines for validation of supervised machine learning models in accelerometer‐based animal behaviour classification

Wilson, O., Schoeman, D. S., Bradley, A. P., & Clemente, C. J. (2025) · Journal of Animal Ecology · doi:10.1111/1365-2656.70054 · Cited by 20

Predictive models for dynamic properties of soils using machine learning approaches: A comprehensive review

Ghorbanzadeh, S., Armaghani, D. J., Salimi, M., & Payan, M. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.113014 · Cited by 18

Machine learning to detect invalid text responses: Validation and comparison to existing detection methods

Yeung, R. C., & Fernandes, M. A. (2022) · Behavior Research Methods · doi:10.3758/s13428-022-01801-y · Cited by 18

Dysarthria detection based on a deep learning model with a clinically-interpretable layer

Xu, L., Liss, J., & Berisha, V. (2023) · JASA Express Letters · doi:10.1121/10.0016833 · Cited by 18

Evolving Memristive Reservoir

Shi, X., Minku, L. L., & Yao, X. (2023) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2023.3270224 · Cited by 19

An Optimized Machine Learning and Deep Learning Framework for Facial and Masked Facial Recognition

Thanathamathee, P., Sawangarreerak, S., Kongkla, P., & Nizam, D. N. M. (2023) · Emerging Science Journal · doi:10.28991/esj-2023-07-04-010 · Cited by 18

Models for forecasting the traffic flow within the city of Ljubljana

Petelin, G., Hribar, R., & Papa, G. (2023) · European Transport Research Review · doi:10.1186/s12544-023-00600-6 · Cited by 20

Identification of serum miR-1246 and miR-150-5p as novel diagnostic biomarkers for high-grade serous ovarian cancer

Niemira, M., Erol, A., Bielska, A., Zeller, A., Skwarska, A., Chwiałkowska, K., Kuźmicki, M., Szamatowicz, J., Reszeć, J., Knapp, P., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-45317-7 · Cited by 18

Prediction of therapy response of breast cancer patients with machine learning based on clinical data and imaging data derived from breast [18F]FDG-PET/MRI

Jannusch, K., Dietzel, F., Bruckmann, N. M., Morawitz, J., Boschheidgen, M., Minko, P., Bittner, A., Mohrmann, S., Quick, H. H., Herrmann, K., et al. (2023) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-023-06513-9 · Cited by 18

Explainable Machine Learning to Unveil Detection Mechanisms with Au Nanoisland-Based Surface-Enhanced Raman Scattering for SARS-CoV-2 Antigen Detection

Pazin, W. M., Furini, L. N., Braz, D. C., Neto, M. P., Fernandes, J. D., Constantino, C. J. L., & Oliveira, O. N. (2024) · ACS Applied Nano Materials · doi:10.1021/acsanm.3c05848 · Cited by 17

Aspect-Based Sentiment Analysis of Arabic Tweets in the Education Sector Using a Hybrid Feature Selection Method

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Real-time Vehicle-Induced Response Identification via crowdsourced labeling for high-frequency unlabeled sensor data

Qi, Z., Wang, Y., Liu, Z., Chao, Z., Dong, Z., & Wang, H. (2026) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2026.113789 · Cited by 16

Building Interpretable Machine Learning Models to Identify Chemometric Trends in Seabirds of the North Pacific Ocean

Mahynski, N. A., Ragland, J. M., Schuur, S. S., & Shen, V. K. (2022) · Environmental Science & Technology · doi:10.1021/acs.est.2c01894 · Cited by 16

Deep Features from Pretrained Networks Do Not Outperform Hand-Crafted Features in Radiomics

Demircioğlu, A. (2023) · Diagnostics · doi:10.3390/diagnostics13203266 · Cited by 18

‘ LinkedIn , LinkedIn on the screen, who is the greatest and smartest ever seen?’: A machine learning approach using valid LinkedIn cues to predict narcissism and intelligence

Härtel, T. M., Schuler, B. A., & Back, M. D. (2024) · Journal of Occupational and Organizational Psychology · doi:10.1111/joop.12531 · Cited by 17

A novel method for favorable zone prediction of conventional hydrocarbon accumulations based on RUSBoosted tree machine learning algorithm

Ma, K., Pang, X., Pang, H., Lv, C., Gao, T., Chen, J., Huo, X., Cong, Q., & Jiang, M. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.119983 · Cited by 17

Application of Machine Learning to Improve Appropriateness of Treatment in an Orthopaedic Setting of Personalized Medicine

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