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- research-articleOctober 2024
Predicting 3D printed plastic part properties: A deep learning approach with thermographic and vibration data fusion
Expert Systems with Applications: An International Journal (EXWA), Volume 255, Issue PBhttps://doi.org/10.1016/j.eswa.2024.124605AbstractAdditive Manufacturing (AM) holds transformative potential for the manufacturing industry, yet its widespread adoption is hindered by inconsistent product properties. This study addresses this challenge by pioneering a novel predictive method to ...
Highlights- Presently, additive manufacturing suffers from inconsistent product properties.
- A novel method assesses in-process sensing impact on part property prediction.
- Thermographic and vibration data are fused to train hybrid CNN-LSTM ...
- research-articleOctober 2024
Consensus modeling: Safer transfer learning for small health systems
Artificial Intelligence in Medicine (AIIM), Volume 154, Issue Chttps://doi.org/10.1016/j.artmed.2024.102899AbstractPredictive modeling is becoming an essential tool for clinical decision support, but health systems with smaller sample sizes may construct suboptimal or overly specific models. Models become over-specific when beside true physiological effects, ...
Highlights- Health systems with inadequate data may build suboptimal or overly specific models.
- Over-specialized models are not robust to institutional changes and can cause harm.
- Consensus modeling reduces over-specialization for small health ...
- research-articleJuly 2024
Adaptive activation functions for predictive modeling with sparse experimental data
Neural Computing and Applications (NCAA), Volume 36, Issue 29Pages 18297–18311https://doi.org/10.1007/s00521-024-10156-8AbstractA pivotal aspect in the design of neural networks lies in selecting activation functions, crucial for introducing nonlinear structures that capture intricate input–output patterns. While the effectiveness of adaptive or trainable activation ...
- ArticleJuly 2024
Development of a VTE Prediction Model Based on Automatically Selected Features in Glioma Patients
- Sergei Leontev,
- Maria Simakova,
- Vitaly Lukinov,
- Konstantin Pishchulov,
- Ilia Derevitskii,
- Levon Abramyan,
- Alexandra Vatian
AbstractVenous thromboembolism (VTE) poses a significant risk to patients undergoing cancer treatment, particularly in the context of advanced and metastatic disease. In the realm of neuro-oncology, the incidence of VTE varies depending on tumor location ...
- research-articleJuly 2024
Virtual Machine Provisioning Within Data Center Host Machines Using Ensemble Model in Cloud Computing Environment
AbstractIn the digital age of exponential data proliferation and growing computing demands, efficient resource management within data centers is crucial. A key challenge is the provisioning of Virtual Machines (VMs), which significantly impacts ...
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- research-articleJuly 2024
Advancing intrauterine adhesion severity prediction: Integrative machine learning approach with hysteroscopic cold knife system, clinical characteristics and hematological parameters
Computers in Biology and Medicine (CBIM), Volume 177, Issue Chttps://doi.org/10.1016/j.compbiomed.2024.108599AbstractIntrauterine Adhesion (IUA) constitute a significant determinant impacting female fertility, potentially leading to infertility, miscarriage, menstrual irregularities, and placental complications. The precise assessment of the severity of IUA is ...
Highlights- Introduction of a novel machine learning model, bTLSMA-SVM-FS, combining an enhanced Slime Mould Algorithm (TLSMA) with Support Vector Machines for predicting the severity of Intrauterine Adhesions (IUA).
- Comprehensive comparative ...
- research-articleJuly 2024
Early prediction of long hospital stay for Intensive Care units readmission patients using medication information
Computers in Biology and Medicine (CBIM), Volume 174, Issue Chttps://doi.org/10.1016/j.compbiomed.2024.108451Abstract ObjectivePredicting Intensive Care Unit (ICU) Length of Stay (LOS) accurately can improve patient wellness, hospital operations, and the health system's financial status. This study focuses on predicting the prolonged ICU LOS (≥3 days) of the ...
Highlights- Predicting the prolonged ICU LOS (equal to or larger than 3 days) of the second admission.
- Utilizing short historical data (first admission only) for early-stage prediction.
- Incorporating medication information in the models.
- ...
- research-articleJune 2024
Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions
AbstractWith the recent wave of digitalization, specifically in the context of safety–critical applications, there has been a growing need for computationally efficient, accurate, generalizable, and trustworthy models. Physics-based models have ...
Highlights- CoSTA is demonstrated to correct modeling errors incurred due to dimensionality reduction in PBMs.
- CoSTA can correct error arising from the linearization of non-linear phenomena.
- CoSTA shows lower model uncertainty than purely data-...
- research-articleMay 2024
Enhanced prediction of parking occupancy through fusion of adaptive neuro-fuzzy inference system and deep learning models
Engineering Applications of Artificial Intelligence (EAAI), Volume 129, Issue Chttps://doi.org/10.1016/j.engappai.2023.107670AbstractWhile predicting parking occupancy is crucial for managing urban congestion, existing models often exhibit gaps in accuracy, uncertainty handling, and integration potential. This study introduces an innovative combination of adaptive neuro-fuzzy ...
Highlights- Fusion models are developed for enhanced parking occupancy prediction.
- The fusion models showcase the capability to capture dynamic trends effectively.
- The fusion models outperform standalone counterparts and seven benchmarks.
- ...
- research-articleFebruary 2024
Data-driven interpretable ensemble learning methods for the prediction of wind turbine power incorporating SHAP analysis
Expert Systems with Applications: An International Journal (EXWA), Volume 237, Issue PAhttps://doi.org/10.1016/j.eswa.2023.121464AbstractWind energy increasingly attracts investment from many countries as a clean and renewable energy source. Since wind energy investment cost is high, the efficiency of a potential wind power plant should be determined using wind power prediction ...
- research-articleFebruary 2024
MsGEN: Measuring generalization of nutrient value prediction across different recipe datasets
Expert Systems with Applications: An International Journal (EXWA), Volume 237, Issue PBhttps://doi.org/10.1016/j.eswa.2023.121507AbstractIn this study, we estimate the generalization of the performance of previously proposed predictive models for nutrient value prediction across different recipe datasets. For this purpose, we introduce a quantitative indicator that determines the ...
Highlights- Generalization in ML is highly related to the distribution of the training data.
- Transferring a predictive model learned on one dataset to another dataset.
- Similarity between distributions of training and unseen data in the feature ...
- research-articleApril 2024
Trans-Balance: Reducing demographic disparity for prediction models in the presence of class imbalance
Journal of Biomedical Informatics (JOBI), Volume 149, Issue Chttps://doi.org/10.1016/j.jbi.2023.104532Abstract Introduction:Risk prediction, including early disease detection, prevention, and intervention, is essential to precision medicine. However, systematic bias in risk estimation caused by heterogeneity across different demographic groups can lead ...
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- research-articleNovember 2023
Exploring the determinants of research performance for early-career researchers: a literature review
AbstractThis survey study explored various determinants used to predict early-career researchers’ future performance. 50 studies and their relevant references were examined from two main perspectives: (1) what relevant studies expected as outcomes of ...
- research-articleFebruary 2024
A semi-supervised approach to unobtrusively predict abnormality in breathing patterns using hydraulic bed sensor data in older adults aging in place
- Pallavi Gupta,
- Jamal Saied Walker,
- Laurel Despins,
- David Heise,
- James Keller,
- Marjorie Skubic,
- Ruhan Yi,
- Grant J. Scott
Journal of Biomedical Informatics (JOBI), Volume 147, Issue Chttps://doi.org/10.1016/j.jbi.2023.104530AbstractShortness of breath is often considered a repercussion of aging in older adults, as respiratory illnesses like COPD C2SHIP/CERT Website: . or respiratory illnesses due to heart-related issues are often ...
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- research-articleNovember 2023
A novel geometric nonlinear reduced order modeling method using multi-fidelity surrogate for real-time structural analysis
Structural and Multidisciplinary Optimization (SPSMO), Volume 66, Issue 11https://doi.org/10.1007/s00158-023-03689-4AbstractFinite element models (FEM) of geometrically nonlinear structures are increasingly computationally expensive as physical systems become more complex. Nonlinear reduced order models (NLROM) are an efficient alternative to simulate the dynamic ...
- research-articleSeptember 2023
Exploiting the adaptive neural fuzzy inference system for predicting the effect of notch depth on elastic new strain-concentration factor under combined loading
Cluster Computing (KLU-CLUS), Volume 27, Issue 3Pages 3055–3073https://doi.org/10.1007/s10586-023-04131-6AbstractIn this paper, a novel machine-learning based models are presented to predict the effect of notch depth on elastic new strain-concentration factor of rectangular bars with single edge U-notch under combined loading of static tension and pure ...
- research-articleSeptember 2023
On-farm soybean seed protein and oil prediction using satellite data
Computers and Electronics in Agriculture (COEA), Volume 212, Issue Chttps://doi.org/10.1016/j.compag.2023.108096Highlights- On-farm soybean seed protein and oil were forecasted using satellite data.
- Best ...
Soybean [Glycine max L. (Merr.)] seed composition is receiving increased attention among farmers, agronomists, and commodity traders. Increasing the ability to predict seed quality traits such as protein and oil at the field level ...
- research-articleSeptember 2023
Composable Workflow for Accelerating Neural Architecture Search Using In Situ Analytics for Protein Classification
- Georgia Channing,
- Ria Patel,
- Paula Olaya,
- Ariel Rorabaugh,
- Osamu Miyashita,
- Silvina Caino-Lores,
- Catherine Schuman,
- Florence Tama,
- Michela Taufer
ICPP '23: Proceedings of the 52nd International Conference on Parallel ProcessingPage 1https://doi.org/10.1145/3605573.3605636Neural architecture search (NAS), which automates the design of neural network (NN) architectures for scientific datasets, requires significant computational resources and time — often on the order of days or weeks of GPU hours and training time. We ...
- research-articleAugust 2023
Federated learning approaches for fuzzy cognitive maps to support clinical decision-making in dengue
Engineering Applications of Artificial Intelligence (EAAI), Volume 123, Issue PBhttps://doi.org/10.1016/j.engappai.2023.106371AbstractFederated learning is a distributed machine learning approach developed to guarantee the privacy and security of data stored on local devices. In healthcare, specifically in diseases of public health interest such as dengue, it is necessary to ...