AIMC Topic: Prospective Studies
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Machine learning for risk stratification in the emergency department (MARS-ED) study protocol for a randomized controlled pilot trial on the implementation of a prediction model based on machine learning technology predicting 31-day mortality in the emergency department.
Scandinavian journal of trauma, resuscitation and emergency medicine
Jan 23, 2024
BACKGROUND: Many prediction models have been developed to help identify emergency department (ED) patients at high risk of poor outcome. However, these models often underperform in clinical practice and their actual clinical impact has hardly ever be...
Evaluation of a deep image-to-image network (DI2IN) auto-segmentation algorithm across a network of cancer centers.
Journal of cancer research and therapeutics
Jan 22, 2024
PURPOSE/OBJECTIVE S: Due to manual OAR contouring challenges, various automatic contouring solutions have been introduced. Historically, common clinical auto-segmentation algorithms used were atlas-based, which required maintaining a library of self-...
Enhancing Nigrosome-1 Sign Identification via Interpretable AI using True Susceptibility Weighted Imaging.
Journal of magnetic resonance imaging : JMRI
Jan 18, 2024
BACKGROUND: Nigrosome 1 (N1), the largest nigrosome region in the ventrolateral area of the substantia nigra pars compacta, is identifiable by the "N1 sign" in long echo time gradient echo MRI. The N1 sign's absence is a vital Parkinson's disease (PD...
Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.
The American journal of gastroenterology
Jan 18, 2024
INTRODUCTION: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colonoscopy. We evaluated the impact of a novel artificial intelligence (AI) system, compared with standard high-definition colonoscopy, for APC measureme...
Percutaneous nephrolithotomy guided by 5G-powered robot-assisted teleultrasound diagnosis system: first clinical experience with a novel tele-assistance approach (IDEAL stage 1).
BMC urology
Jan 18, 2024
BACKGROUND: To demonstrate the technical feasibility of percutaneous nephrolithotomy (PCNL) guided by 5G-powered robot-assisted teleultrasound diagnosis system (RTDS) in a complex kidney-stone (CKS) cohort and present our preliminary outcomes. PCNL i...
Validation of reliability, repeatability and consistency of three-dimensional choroidal vascular index.
Scientific reports
Jan 18, 2024
This study aimed to investigate the reliability, repeatability and consistency of choroidal vascularity index (CVI) measurements provided by an artificial intelligence-based software in swept-source optical coherence tomography (SS-OCT) in normal sub...
A Machine Learning Approach to Predict Post-stroke Fatigue. The Nor-COAST study.
Archives of physical medicine and rehabilitation
Jan 17, 2024
OBJECTIVE: This study aimed to predict fatigue 18 months post-stroke by utilizing comprehensive data from the acute and sub-acute phases after stroke in a machine-learning set-up.
ChatGPT in Medical Education: A Precursor for Automation Bias?
JMIR medical education
Jan 17, 2024
Artificial intelligence (AI) in health care has the promise of providing accurate and efficient results. However, AI can also be a black box, where the logic behind its results is nonrational. There are concerns if these questionable results are used...
Prediction of preeclampsia from retinal fundus images via deep learning in singleton pregnancies: a prospective cohort study.
Journal of hypertension
Jan 15, 2024
INTRODUCTION: Early prediction of preeclampsia (PE) is of universal importance in controlling the disease process. Our study aimed to assess the feasibility of using retinal fundus images to predict preeclampsia via deep learning in singleton pregnan...
Predictive Minisci late stage functionalization with transfer learning.
Nature communications
Jan 15, 2024
Structural diversification of lead molecules is a key component of drug discovery to explore chemical space. Late-stage functionalizations (LSFs) are versatile methodologies capable of installing functional handles on richly decorated intermediates t...
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