AIMC Journal:
Journal of the American Medical Informatics Association : JAMIA

Showing 471 to 480 of 493 articles

Expanding a radiology lexicon using contextual patterns in radiology reports.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Distributional semantics algorithms, which learn vector space representations of words and phrases from large corpora, identify related terms based on contextual usage patterns. We hypothesize that distributional semantics can speed up lex...

SemEHR: A general-purpose semantic search system to surface semantic data from clinical notes for tailored care, trial recruitment, and clinical research.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Unlocking the data contained within both structured and unstructured components of electronic health records (EHRs) has the potential to provide a step change in data available for secondary research use, generation of actionable medical i...

Using machine learning for sequence-level automated MRI protocol selection in neuroradiology.

Journal of the American Medical Informatics Association : JAMIA
Incorrect imaging protocol selection can lead to important clinical findings being missed, contributing to both wasted health care resources and patient harm. We present a machine learning method for analyzing the unstructured text of clinical indica...

Characteristics of knowledge content in a curated online evidence library.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation.

Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.

Journal of the American Medical Informatics Association : JAMIA
We propose Segment Convolutional Neural Networks (Seg-CNNs) for classifying relations from clinical notes. Seg-CNNs use only word-embedding features without manual feature engineering. Unlike typical CNN models, relations between 2 concepts are ident...

NLPReViz: an interactive tool for natural language processing on clinical text.

Journal of the American Medical Informatics Association : JAMIA
The gap between domain experts and natural language processing expertise is a barrier to extracting understanding from clinical text. We describe a prototype tool for interactive review and revision of natural language processing models of binary con...

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects ...

Mining e-cigarette adverse events in social media using Bi-LSTM recurrent neural network with word embedding representation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Recent years have seen increased worldwide popularity of e-cigarette use. However, the risks of e-cigarettes are underexamined. Most e-cigarette adverse event studies have achieved low detection rates due to limited subject sample sizes in...

Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make th...

Calibration drift in regression and machine learning models for acute kidney injury.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Predictive analytics create opportunities to incorporate personalized risk estimates into clinical decision support. Models must be well calibrated to support decision-making, yet calibration deteriorates over time. This study explored the...