[HTML][HTML] Clinical information extraction applications: a literature review
Background With the rapid adoption of electronic health records (EHRs), it is desirable to
harvest information and knowledge from EHRs to support automated systems at the point of …
harvest information and knowledge from EHRs to support automated systems at the point of …
Artificial intelligence in cardiology: present and future
Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of
various types but most often to deep neural networks. Cardiology is at the forefront of AI in …
various types but most often to deep neural networks. Cardiology is at the forefront of AI in …
Causes and mechanisms of isolated mitral regurgitation in the community: clinical context and outcome
Aims To define the hitherto unknown aetiology/mechanism distributions of mitral
regurgitation (MR) in the community and the linked clinical characteristics/outcomes …
regurgitation (MR) in the community and the linked clinical characteristics/outcomes …
Outcome and undertreatment of mitral regurgitation: a community cohort study
Background Mitral regurgitation is the most common valve disease worldwide but whether
the community-wide prevalence, poor patient outcomes, and low rates of surgical treatment …
the community-wide prevalence, poor patient outcomes, and low rates of surgical treatment …
A clinical text classification paradigm using weak supervision and deep representation
Background Automatic clinical text classification is a natural language processing (NLP)
technology that unlocks information embedded in clinical narratives. Machine learning …
technology that unlocks information embedded in clinical narratives. Machine learning …
Advances in electronic phenoty**: from rule-based definitions to machine learning models
With the widespread adoption of electronic health records (EHRs), large repositories of
structured and unstructured patient data are becoming available to conduct observational …
structured and unstructured patient data are becoming available to conduct observational …
[HTML][HTML] Clinical concept extraction: a methodology review
Background Concept extraction, a subdomain of natural language processing (NLP) with a
focus on extracting concepts of interest, has been adopted to computationally extract clinical …
focus on extracting concepts of interest, has been adopted to computationally extract clinical …
[HTML][HTML] Clinical data reuse or secondary use: current status and potential future progress
Objective: To perform a review of recent research in clinical data reuse or secondary use,
and envision future advances in this field. Methods: The review is based on a large literature …
and envision future advances in this field. Methods: The review is based on a large literature …
An overview of biomedical entity linking throughout the years
Abstract Biomedical Entity Linking (BEL) is the task of map** of spans of text within
biomedical documents to normalized, unique identifiers within an ontology. This is an …
biomedical documents to normalized, unique identifiers within an ontology. This is an …
[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …