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Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information.

Sensors (Basel, Switzerland)
The deterioration of infrastructure's health has become more predominant on a global scale during the 21st century. Aging infrastructure as well as those structures damaged by natural disasters have prompted the research community to improve state-of...

Abnormality classification and localization using dual-branch whole-region-based CNN model with histopathological images.

Computers in biology and medicine
The task of classification and localization with detecting abnormalities in medical images is considered very challenging. Computer-aided systems have been widely employed to address this issue, and the proliferation of deep learning network architec...

Semi-supervised learning framework for oil and gas pipeline failure detection.

Scientific reports
Quantifying failure events of oil and gas pipelines in real- or near-real-time facilitates a faster and more appropriate response plan. Developing a data-driven pipeline failure assessment model, however, faces a major challenge; failure history, in ...

The Leaf Clinical Trials Corpus: a new resource for query generation from clinical trial eligibility criteria.

Scientific data
Identifying cohorts of patients based on eligibility criteria such as medical conditions, procedures, and medication use is critical to recruitment for clinical trials. Such criteria are often most naturally described in free-text, using language fam...

An efficient modular framework for automatic LIONC classification of MedIMG using unified medical language.

Frontiers in public health
Handwritten prescriptions and radiological reports: doctors use handwritten prescriptions and radiological reports to give drugs to patients who have illnesses, injuries, or other problems. Clinical text data, like physician prescription visuals and ...

Analysis of e-Mail Spam Detection Using a Novel Machine Learning-Based Hybrid Bagging Technique.

Computational intelligence and neuroscience
e-mail service providers and consumers find it challenging to distinguish between spam and nonspam e-mails. The purpose of spammers is to spread false information by sending annoying messages that catch the attention of the public. Various spam ident...

Healthcare data integration using machine learning: A case study evaluation with health information-seeking behavior databases.

Research in social & administrative pharmacy : RSAP
BACKGROUND: The amount of data in health care is rapidly rising, leading to multiple datasets generated for any given individual. Data integration involves mapping variables in different datasets together to form a combined dataset which can then be ...

A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection.

IEEE/ACM transactions on computational biology and bioinformatics
The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance, which provides effective and safe co-prescriptions of multiple drugs. Since laboratory researches are often complicated, costly and time-consuming, it's ur...

Active Fine-Tuning From gMAD Examples Improves Blind Image Quality Assessment.

IEEE transactions on pattern analysis and machine intelligence
The research in image quality assessment (IQA) has a long history, and significant progress has been made by leveraging recent advances in deep neural networks (DNNs). Despite high correlation numbers on existing IQA datasets, DNN-based models may be...

AsthmaKGxE: An asthma-environment interaction knowledge graph leveraging public databases and scientific literature.

Computers in biology and medicine
MOTIVATION: Asthma is a complex heterogeneous disease resulting from intricate interactions between genetic and non-genetic factors related to environmental and psychosocial aspects. Discovery of such interactions can provide insights into the pathop...