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data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
level learning » deep learning (Expand Search)
rd algorithm » _ algorithms (Expand Search)
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101
Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers
Published 2024“…In this study, we developed an interpretable machine learning model leveraging baseline levels of biomarkers of oxidative stress (OS), inflammation, and mitochondrial dysfunction (MD) for identifying individuals at risk of developing T2DM. …”
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102
A hybrid approach for XML similarity
Published 2007“…Various algorithms for comparing hierarchically structured data, e.g. …”
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conferenceObject -
103
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Dedicated weighting functions and various search algorithms have been developed for that purpose and will be presented here. …”
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104
Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
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doctoralThesis -
105
On the complexity of multi-parameterized cluster editing
Published 2017“…In other words, Cluster Editing can be solved efficiently when the number of false positives/negatives per single data element is expected to be small compared to the minimum cluster size. …”
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106
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…In this paper, we present an automatic tool that uses machine learning techniques to predict the development of type 2 diabetes mellitus (T2DM). …”
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107
Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review
Published 2025“…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …”
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108
Software defect prediction. (c2019)
Published 2019“…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). We compare our approach to 9 well known machine learning techniques and results show the advantages of our model over the other techniques. …”
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masterThesis -
109
A Fully Optical Laser Based System for Damage Detection and Localization in Rail Tracks Using Ultrasonic Rayleigh Waves: A Numerical and Experimental Study
Published 2022“…Fifth, it is also observed that the actuation and sensing position plays a crucial role in receiving the time-domain data with a sufficient SNR and the one that is easy to analyze and interpret. …”
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110
A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks
Published 2022“…Experimental results on simulated and real datasets collected at two regions, which have extremely different climate conditions, confirm that the proposed deep micro-moment architecture outperforms other machine learning algorithms and can effectively detect anomalous patterns. …”
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111
Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases
Published 2024“…However, the ECG can be interpreted differently by humans depending on the interpreter's level of training and experience, which could make diagnosis more difficult. …”
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112
Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3
Published 2020“…Deep learning algorithms have demonstrated remarkable performance in many sectors and have become one of the main foundations of modern computer-vision solutions. …”
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conferenceObject -
113
On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity
Published 2020“…Simulation results are presented for both parts of the thesis to illustrate the effectiveness of the proposed solutions and algorithms in comparison with optimal solutions and baseline algorithms.…”
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masterThesis -
114
Urinary Metabolomic Markers of Protein Glycation, Oxidation, and Nitration in Early-Stage Decline in Metabolic, Vascular, and Renal Health
Published 2019“…Urinary amino acid metabolites were determined by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry. Machine learning was applied to optimise and validate algorithms to discriminate between study groups for potential diagnostic utility. …”
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115
Exploring the Dynamic Interplay of Deleterious Variants on the RAF1–RAP1A Binding in Cancer: Conformational Analysis, Binding Free Energy, and Essential Dynamics
Published 2024“…Integrated machine learning algorithms showed that among the 134 mutations reported for these 2 proteins, only 13 and 35 were classified as deleterious mutations in <i>RAF1</i> and <i>RAP1P</i>, respectively. …”
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117
Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
Published 2017Get full text
doctoralThesis