AI Medical Compendium Topic

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Terminology as Topic

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A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The Unified Medical Language System (UMLS) integrates various source terminologies to support interoperability between biomedical information systems. In this article, we introduce a novel transformation-based auditing method that leverage...

A graph-based method for reconstructing entities from coordination ellipsis in medical text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Coordination ellipsis is a linguistic phenomenon abound in medical text and is challenging for concept normalization because of difficulty in recognizing elliptical expressions referencing 2 or more entities accurately. To resolve this bot...

Classification Techniques for Cardio-Vascular Diseases Using Supervised Machine Learning.

Medical archives (Sarajevo, Bosnia and Herzegovina)
INTRODUCTION: The World Health Organization has estimated that 12 million deaths occur worldwide, every year due to Heart diseases. Half the deaths in the developed countries are due to cardiovascular diseases. The early prognosis of cardiovascular d...

[Machine learning in radiology : Terminology from individual timepoint to trajectory].

Der Radiologe
METHODICAL ISSUE: Machine learning (ML) algorithms have an increasingly relevant role in radiology tackling tasks such as the automatic detection and segmentation of diagnosis-relevant markers, the quantification of progression and response, and thei...

Adverse drug event and medication extraction in electronic health records via a cascading architecture with different sequence labeling models and word embeddings.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: An adverse drug event (ADE) refers to an injury resulting from medical intervention related to a drug including harm caused by drugs or from the usage of drugs. Extracting ADEs from clinical records can help physicians associate adverse ev...

What is Machine Learning? A Primer for the Epidemiologist.

American journal of epidemiology
Machine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problems for which classical methods are not well-suited. I...

Neural machine translation of clinical texts between long distance languages.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To analyze techniques for machine translation of electronic health records (EHRs) between long distance languages, using Basque and Spanish as a reference. We studied distinct configurations of neural machine translation systems and used d...

Automatic Normalization of Anatomical Phrases in Radiology Reports Using Unsupervised Learning.

Journal of digital imaging
In today's radiology workflow, free-text reporting is established as the most common medium to capture, store, and communicate clinical information. Radiologists routinely refer to prior radiology reports of a patient to recall critical information f...

Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics.

Anesthesia and analgesia
Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical ca...