AI Medical Compendium Topic

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Machine learning-based analysis for prediction of surgical necrotizing enterocolitis in very low birth weight infants using perinatal factors: a nationwide cohort study.

European journal of pediatrics
Early prediction of surgical necrotizing enterocolitis (sNEC) in preterm infants is important. However, owing to the complexity of the disease, identifying infants with NEC at a high risk for surgical intervention is difficult. We developed a machine...

Using machine learning to predict outcomes of patients with blunt traumatic aortic injuries.

The journal of trauma and acute care surgery
BACKGROUND: The optimal management of blunt thoracic aortic injury (BTAI) remains controversial, with experienced centers offering therapy ranging from medical management to TEVAR. We investigated the utility of a machine learning (ML) algorithm to d...

Building large-scale registries from unstructured clinical notes using a low-resource natural language processing pipeline.

Artificial intelligence in medicine
Building clinical registries is an important step in clinical research and improvement of patient care quality. Natural Language Processing (NLP) methods have shown promising results in extracting valuable information from unstructured clinical notes...

Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.

Clinical orthopaedics and related research
BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling a...

A practical guide to the development and deployment of deep learning models for the orthopaedic surgeon: Part III, focus on registry creation, diagnosis, and data privacy.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Deep learning is a subset of artificial intelligence (AI) with enormous potential to transform orthopaedic surgery. As has already become evident with the deployment of Large Language Models (LLMs) like ChatGPT (OpenAI Inc.), deep learning can rapidl...

The importance of data in Pulmonary Arterial Hypertension: from international registries to Machine Learning.

Medicina clinica
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
OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive techniques (ART).

Neurologic Statistical Prognostication and Risk Assessment for Kids on Extracorporeal Membrane Oxygenation-Neuro SPARK.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
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
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.