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lacking algorithm » learning algorithms (Expand Search)
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61
Predicting Android Malware Using Evolution Networks
Published 2025“…This issue requires the development of efficient solutions in order to keep up with the continuous evolution of malware. …”
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masterThesis -
62
Improving Rule Set Based Software Quality Prediction
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63
Positive Unlabelled Learning to Recognize Dishes as Named Entity
Published 2019“…In this research, I focus on extracting food and dish names as a named entity. With the lack of labelled data, I try to overcome the cold start and avoid manual labelling by building a lookup table from a dictionary. …”
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A hybrid approach for XML similarity
Published 2007“…Various algorithms for comparing hierarchically structured data, e.g. …”
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conferenceObject -
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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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Machine Learning-Based Approach for EV Charging Behavior
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doctoralThesis -
68
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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Molecular Classification of Breast Cancer Utilizing Long Non-Coding RNA (lncRNA) Transcriptomes Identifies Novel Diagnostic lncRNA Panel for Triple-Negative Breast Cancer
Published 2021“…In the current study, we utilize RNA sequencing data to identify lncRNA-based biomarkers associated with TNBC, ER+ subtypes, and normal breast tissue. …”
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71
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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72
Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma
Published 2019“…<h3>Background</h3><p dir="ltr">Predictive modeling with longitudinal electronic health record (EHR) data offers great promise for accelerating personalized medicine and better informs clinical decision-making. …”
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Barriers of Adopting Artificial Intelligence Tools in Engineering Construction Projects
Published 2023“…Construction data management and integration are difficult. AI algorithms depend on data for training and analysis. …”
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74
Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes
Published 2023“…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER<sup>+</sup>), HER2<sup>+</sup>, ER<sup>+</sup>HER2<sup>+</sup>, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …”
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Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Cyberbullying involves the use of communication technology and data, including messages, photographs, and videos, to undertake aggressive negative actions to harm others. …”
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THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar
Published 2020“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. …”
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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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Towards secure and trusted AI in healthcare: A systematic review of emerging innovations and ethical challenges
Published 2025“…According to several studies, more than 60 % of healthcare professionals have expressed their hesitation in adopting AI systems due to a lack of transparency and fear of data insecurity. …”
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Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications
Published 2017Get full text
doctoralThesis