AIMC Topic: Databases, Factual

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Enhancing clinical concept extraction with contextual embeddings.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Recently, however, more advanced embedding methods and represe...

Optimizing clinical trials recruitment via deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Clinical trials, prospective research studies on human participants carried out by a distributed team of clinical investigators, play a crucial role in the development of new treatments in health care. This is a complex and expensive proce...

Biomedical image augmentation using Augmentor.

Bioinformatics (Oxford, England)
MOTIVATION: Image augmentation is a frequently used technique in computer vision and has been seeing increased interest since the popularity of deep learning. Its usefulness is becoming more and more recognized due to deep neural networks requiring l...

[An overview of validation methods based on the medical claims database].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Medical claims database is an important source of data for studying the characteristics, and burden of diseases, to provide a basis for the development of policy on management. The database is usually used to identify patients through International C...

Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets.

Journal of biomedical optics
We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravascular optical coherence tomography (IVOCT) images using a comprehensive set of handcrafted features. We incorporated features developed in previous st...

Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Electronic medical records (EMRs) and population-based cancer registries contain information on cancer outcomes and treatment, yet rarely capture information on the timing of metastatic cancer recurrence, which is essential to understand can...

Fast and Precise Hippocampus Segmentation Through Deep Convolutional Neural Network Ensembles and Transfer Learning.

Neuroinformatics
Automatic segmentation of the hippocampus from 3D magnetic resonance imaging mostly relied on multi-atlas registration methods. In this work, we exploit recent advances in deep learning to design and implement a fully automatic segmentation method, o...

Comprehensive Word-Level Classification of Screening Mammography Reports Using a Neural Network Sequence Labeling Approach.

Journal of digital imaging
Radiology reports contain a large amount of potentially valuable unstructured data. Recently, neural networks have been employed to perform classification of radiology reports over a few classes at the document level. The success of neural networks i...