AIMC Topic: Electronic Health Records

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Streams, rivers and data lakes: an introduction to understanding modern electronic healthcare records.

Clinical medicine (London, England)
As foundation doctors, we have often found ourselves informing patients that a certain aspect of their medical information cannot be immediately found, either because it is on an electronic system we cannot access, or it is in a hospital that is unli...

PPAD: a deep learning architecture to predict progression of Alzheimer's disease.

Bioinformatics (Oxford, England)
MOTIVATION: Alzheimer's disease (AD) is a neurodegenerative disease that affects millions of people worldwide. Mild cognitive impairment (MCI) is an intermediary stage between cognitively normal state and AD. Not all people who have MCI convert to AD...

The Progress of Speech Recognition in Health Care: Surgery as an Example.

Studies in health technology and informatics
Artificial Intelligence (AI) is a computer system that simulates intelligent human behavior. The use of AI is rapidly shifting Healthcare. Speech recognition (SR) is a type of AI physicians use to operate Electronic Health records (EHR). This paper a...

quEHRy: a question answering system to query electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We propose a system, quEHRy, to retrieve precise, interpretable answers to natural language questions from structured data in electronic health records (EHRs).

A Masked Language Model for Multi-Source EHR Trajectories Contextual Representation Learning.

Studies in health technology and informatics
Using electronic health records data and machine learning to guide future decisions needs to address challenges, including 1) long/short-term dependencies and 2) interactions between diseases and interventions. Bidirectional transformers have effecti...

Domain Knowledge-Driven Generation of Synthetic Healthcare Data.

Studies in health technology and informatics
Healthcare longitudinal data collected around patients' life cycles, today offer a multitude of opportunities for healthcare transformation utilizing artificial intelligence algorithms. However, access to "real" healthcare data is a big challenge due...

Clustering Similar Diagnosis Terms.

Studies in health technology and informatics
A large clinical diagnosis list is explored with the goal to cluster syntactic variants. A string similarity heuristic is compared with a deep learning-based approach. Levenshtein distance (LD) applied to common words only (not tolerating deviations ...

Data-Driven Identification of Clinical Real-World Expressions Linked to ICD.

Studies in health technology and informatics
A semi-structured clinical problem list containing ∼1.9 million de-identified entries linked to ICD-10 codes was used to identify closely related real-world expressions. A log-likelihood based co-occurrence analysis generated seed-terms, which were i...

In-Hospital Cancer Mortality Prediction by Multimodal Learning of Non-English Clinical Texts.

Studies in health technology and informatics
Predicting important outcomes in patients with complex medical conditions using multimodal electronic medical records remains challenge. We trained a machine learning model to predict the inpatient prognosis of cancer patients using EMR data with Jap...

Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment.

Studies in health technology and informatics
Clinical information systems have become large repositories for semi-structured and partly annotated electronic health record data, which have reached a critical mass that makes them interesting for supervised data-driven neural network approaches. W...