[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 …
Natural language processing in radiology: a systematic review
Radiological reporting has generated large quantities of digital content within the electronic
health record, which is potentially a valuable source of information for improving clinical care …
health record, which is potentially a valuable source of information for improving clinical care …
Comparative effectiveness of convolutional neural network (CNN) and recurrent neural network (RNN) architectures for radiology text report classification
This paper explores cutting-edge deep learning methods for information extraction from
medical imaging free text reports at a multi-institutional scale and compares them to the state …
medical imaging free text reports at a multi-institutional scale and compares them to the state …
Impact of artificial intelligence on interventional cardiology: from decision-making aid to advanced interventional procedure assistance
Access to big data analyzed by supercomputers using advanced mathematical algorithms
(ie, deep machine learning) has allowed for enhancement of cognitive output (ie, visual …
(ie, deep machine learning) has allowed for enhancement of cognitive output (ie, visual …
[HTML][HTML] The revival of the notes field: leveraging the unstructured content in electronic health records
Problem: Clinical practice requires the production of a time-and resource-consuming great
amount of notes. They contain relevant information, but their secondary use is almost …
amount of notes. They contain relevant information, but their secondary use is almost …
MedXN: an open source medication extraction and normalization tool for clinical text
Abstract Objective We developed the Medication Extraction and Normalization (MedXN)
system to extract comprehensive medication information and normalize it to the most …
system to extract comprehensive medication information and normalize it to the most …
[HTML][HTML] Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort
We proposed an unsupervised hybrid method–Intelligent Word Embedding (IWE) that
combines neural embedding method with a semantic dictionary mapping technique for …
combines neural embedding method with a semantic dictionary mapping technique for …
Artificial intelligence in cardiology
D Itchhaporia - Trends in cardiovascular medicine, 2022 - Elsevier
This review examines the current state and application of artificial intelligence (AI) and
machine learning (ML) in cardiovascular medicine. AI is changing the clinical practice of …
machine learning (ML) in cardiovascular medicine. AI is changing the clinical practice of …
Use of natural language processing algorithms to identify common data elements in operative notes for total hip arthroplasty
Background: Manual chart review is labor-intensive and requires specialized knowledge
possessed by highly trained medical professionals. Natural language processing (NLP) …
possessed by highly trained medical professionals. Natural language processing (NLP) …
Clinical documentation variations and NLP system portability: a case study in asthma birth cohorts across institutions
Objective To assess clinical documentation variations across health care institutions using
different electronic medical record systems and investigate how they affect natural language …
different electronic medical record systems and investigate how they affect natural language …