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lacking algorithm » learning algorithms (Expand Search)
mining algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
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101
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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102
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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103
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104
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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105
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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106
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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107
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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108
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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109
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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110
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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111
Developing an online hate classifier for multiple social media platforms
Published 2020“…Although researchers have found that hate is a problem across multiple platforms, there is a lack of models for online hate detection using multi-platform data. …”
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112
A Framework for Predictive Modeling in Sustainable Projects
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113
Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases
Published 2024“…Potentially disregarded age-related ECG variations may result from skewed age data in training sets. ECG patterns are affected by physiological differences between the sexes; a dataset that is inclined toward one sex may compromise the accuracy of the others. …”
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114
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…<h3>Background</h3><p dir="ltr">Research gaps refer to unanswered questions in the existing body of knowledge, either due to a lack of studies or inconclusive results. Research gaps are essential starting points and motivation in scientific research. …”