AIMC Topic: Registries
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The importance of data in Pulmonary Arterial Hypertension: from international registries to Machine Learning.
Medicina clinica
Feb 20, 2024
Real-world registries have been critical to building the scientific knowledge of rare diseases, including Pulmonary Arterial Hypertension (PAH). In the past 4 decades, a considerable number of registries on this condition have allowed to improve the ...
Prediction of pregnancy-related complications in women undergoing assisted reproduction, using machine learning methods.
Fertility and sterility
Feb 17, 2024
OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive techniques (ART).
Artificial intelligence (AI) and large data registries: Understanding the advantages and limitations of contemporary data sets for use in AI research.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Jan 3, 2024
Neurologic Statistical Prognostication and Risk Assessment for Kids on Extracorporeal Membrane Oxygenation-Neuro SPARK.
ASAIO journal (American Society for Artificial Internal Organs : 1992)
Dec 21, 2023
This study presents Neuro-SPARK, the first scoring system developed to assess the risk of neurologic injury in pediatric and neonatal patients on extracorporeal membrane oxygenation (ECMO). Using the extracorporeal life support organization (ELSO) re...
Anti-mutated citrullinated vimentin antibodies are increased in IPF patients.
Respiratory medicine and research
Dec 14, 2023
INTRO: An increased prevalence of serum anti-MCV antibody is observed in the serum of patients with idiopathic pulmonary fibrosis (IPF) but the clinical relevance of these antibodies is unknown.
Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis.
Journal of cancer survivorship : research and practice
Dec 7, 2023
PURPOSE: To prevent (chronic) cancer-related fatigue (CRF) after breast cancer, it is important to identify survivors at risk on time. In literature, factors related to CRF are identified, but not often linked to individual risks. Therefore, our aim ...
Leveraging automated approaches to categorize birth defects from abstracted birth hospitalization data.
Birth defects research
Nov 6, 2023
BACKGROUND: The Surveillance for Emerging Threats to Pregnant People and Infants Network (SET-NET) collects data abstracted from medical records and birth defects registries on pregnant people and their infants to understand outcomes associated with ...
[The Swecrit Biobank, associated clinical registries, and machine learning (artificial intelligence) improve critical care knowledge].
Lakartidningen
Oct 16, 2023
The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, trauma, and COVID-19 include more than 150,000 blood samples and descriptions of critically ill patients. These assets provide a unique opportunity to...
Machine Learning for the Prediction of Survival Post-Allogeneic Hematopoietic Cell Transplantation: A Single-Center Experience.
Acta haematologica
Sep 28, 2023
INTRODUCTION: Prediction of outcomes following allogeneic hematopoietic cell transplantation (HCT) remains a major challenge. Machine learning (ML) is a computational procedure that may facilitate the generation of HCT prediction models. We sought to...
Learning curves and procedural times in Senhance®-robotic assisted fundoplication: results from 237 consecutive patients undergoing robotic fundoplication in a single center as part of the European TRUST Robotic Surgery Registry Study.
Surgical endoscopy
Sep 5, 2023
BACKGROUND: Gastroesophageal reflux disease requiring an operative solution is common. Minimally invasive surgery to generate an anti-reflux barrier at the distal esophagus following the principle of the "floppy Nissen" technique has become the gold ...
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