AIMC Topic: Registries

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Arrhythmic Mitral Valve Prolapse Phenotype: An Unsupervised Machine Learning Analysis Using a Multicenter Cardiac MRI Registry.

Radiology. Cardiothoracic imaging
Purpose To use unsupervised machine learning to identify phenotypic clusters with increased risk of arrhythmic mitral valve prolapse (MVP). Materials and Methods This retrospective study included patients with MVP without hemodynamically significant ...

Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The timely stratification of trauma injury severity can enhance the quality of trauma care but it requires intense manual annotation from certified trauma coders. The objective of this study is to develop machine learning models for the st...

DOME Registry: implementing community-wide recommendations for reporting supervised machine learning in biology.

GigaScience
Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The Data Optimization Model Evaluation (DOME) recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for...

DeepPhe-CR: Natural Language Processing Software Services for Cancer Registrar Case Abstraction.

JCO clinical cancer informatics
PURPOSE: Manual extraction of case details from patient records for cancer surveillance is a resource-intensive task. Natural Language Processing (NLP) techniques have been proposed for automating the identification of key details in clinical notes. ...

The time is now: making the case for a UK registry of deployment of radiology artificial intelligence applications.

Clinical radiology
Artificial intelligence (AI)-based healthcare applications (apps) are rapidly evolving, and radiology is a target specialty for their implementation. In this paper, we put the case for a national deployment registry to track the spread of AI apps int...

A web-based tool for automatically linking clinical trials to their publications.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Evidence synthesis teams, physicians, policy makers, and patients and their families all have an interest in following the outcomes of clinical trials and would benefit from being able to evaluate both the results posted in trial registrie...

Predicting Anterior Cruciate Ligament Reconstruction Revision: A Machine Learning Analysis Utilizing the Norwegian Knee Ligament Register.

The Journal of bone and joint surgery. American volume
BACKGROUND: Several factors are associated with an increased risk of anterior cruciate ligament (ACL) reconstruction revision. However, the ability to accurately translate these factors into a quantifiable risk of revision at a patient-specific level...

Optimal vocabulary selection approaches for privacy-preserving deep NLP model training for information extraction and cancer epidemiology.

Cancer biomarkers : section A of Disease markers
BACKGROUND: With the use of artificial intelligence and machine learning techniques for biomedical informatics, security and privacy concerns over the data and subject identities have also become an important issue and essential research topic. Witho...

Development and validation of an artificial neural network algorithm to predict mortality and admission to hospital for heart failure after myocardial infarction: a nationwide population-based study.

The Lancet. Digital health
BACKGROUND: Patients have an estimated mortality of 15-20% within the first year following myocardial infarction and one in four patients who survive myocardial infarction will develop heart failure, severely reducing quality of life and increasing t...