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Big data and machine learning in critical care: Opportunities for collaborative research.
Medicina intensiva
Aug 2, 2018
The introduction of clinical information systems (CIS) in Intensive Care Units (ICUs) offers the possibility of storing a huge amount of machine-ready clinical data that can be used to improve patient outcomes and the allocation of resources, as well...
RETRACTED: Diagnosis labeling with disease-specific characteristics mining.
Artificial intelligence in medicine
Jul 31, 2018
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of the authors; serious errors had been introd...
Mining features for biomedical data using clustering tree ensembles.
Journal of biomedical informatics
Jul 29, 2018
The volume of biomedical data available to the machine learning community grows very rapidly. A rational question is how informative these data really are or how discriminant the features describing the data instances are. Several biomedical datasets...
Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural Networks.
Annals of biomedical engineering
Jul 26, 2018
The tumor-stroma ratio (TSR) reflected on hematoxylin and eosin (H&E)-stained histological images is a potential prognostic factor for survival. Automatic image processing techniques that allow for high-throughput and precise discrimination of tumor ...
Complex-valued unsupervised convolutional neural networks for sleep stage classification.
Computer methods and programs in biomedicine
Jul 26, 2018
BACKGROUND AND OBJECTIVE: Despite numerous deep learning methods being developed for automatic sleep stage classification, almost all the models need labeled data. However, obtaining labeled data is a subjective process. Therefore, the labels will be...
Supervised Segmentation of Un-Annotated Retinal Fundus Images by Synthesis.
IEEE transactions on medical imaging
Jul 24, 2018
We focus on the practical challenge of segmenting new retinal fundus images that are dissimilar to existing well-annotated data sets. It is addressed in this paper by a supervised learning pipeline, with its core being the construction of a synthetic...
3D-Aided Dual-Agent GANs for Unconstrained Face Recognition.
IEEE transactions on pattern analysis and machine intelligence
Jul 23, 2018
Synthesizing realistic profile faces is beneficial for more efficiently training deep pose-invariant models for large-scale unconstrained face recognition, by augmenting the number of samples with extreme poses and avoiding costly annotation work. Ho...
Deep Generative Adversarial Neural Networks for Compressive Sensing MRI.
IEEE transactions on medical imaging
Jul 23, 2018
Undersampled magnetic resonance image (MRI) reconstruction is typically an ill-posed linear inverse task. The time and resource intensive computations require tradeoffs between accuracy and speed. In addition, state-of-the-art compressed sensing (CS)...
Utilizing Big Data in Cancer Care.
Surgical oncology clinics of North America
Jul 23, 2018
Clinical research has boomed over the past decade, with the development of multiple clinical datasets that are available for retrospective review. However, data remain incomplete based on fragmented reporting, provider change, and loss of follow-up. ...
Automatic extraction of protein-protein interactions using grammatical relationship graph.
BMC medical informatics and decision making
Jul 23, 2018
BACKGROUND: Relationships between bio-entities (genes, proteins, diseases, etc.) constitute a significant part of our knowledge. Most of this information is documented as unstructured text in different forms, such as books, articles and on-line pages...
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