AIMC Topic: Retrospective Studies

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Hybrid Method Incorporating a Rule-Based Approach and Deep Learning for Prescription Error Prediction.

Drug safety
INTRODUCTION: Recently, automated detection has been a new approach to address the risks posed by prescribing errors. This study focused on prescription errors and utilized real medical data to supplement the Drug Utilization Review (DUR)-based rules...

Artificial Intelligence Assessment of Renal Scarring (AIRS Study).

Kidney360
BACKGROUND: The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for noninvasive quantification of kidney fibrosis from imaging scans.

Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising acc...

Automatic Forecasting of Radiology Examination Volume Trends for Optimal Resource Planning and Allocation.

Journal of digital imaging
The aim of the study was to evaluate the performance of the Prophet forecasting procedure, part of the Facebook open-source Artificial Intelligence portfolio, for forecasting variations in radiological examination volumes. Daily CT and MRI examinatio...

A maChine and deep Learning Approach to predict pulmoNary hyperteNsIon in newbornS with congenital diaphragmatic Hernia (CLANNISH): Protocol for a retrospective study.

PloS one
INTRODUCTION: Outcome predictions of patients with congenital diaphragmatic hernia (CDH) still have some limitations in the prenatal estimate of postnatal pulmonary hypertension (PH). We propose applying Machine Learning (ML), and Deep Learning (DL) ...

Association of Gastroesophageal Reflux Disease with Preterm Birth: Machine Learning Analysis.

Journal of Korean medical science
BACKGROUND: This study used machine learning and population data for testing the associations of preterm birth with gastroesophageal reflux disease (GERD) and periodontitis.

Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

Medical physics
PURPOSE: This study aimed to explore the predictive ability of deep learning (DL) for the common epidermal growth factor receptor (EGFR) mutation subtypes in patients with lung adenocarcinoma.

Mandate to evaluate robotic surgery implementation: a 12-year retrospective analysis of impact and future implications.

Journal of robotic surgery
The introduction of robotic surgery in hospitals has raised much debate given the various effects on care, costs, education and medical advancement. Purchasing discussions are often approached with more questions than answers and there is a need for ...

Development and Validation of a Deep Learning Strategy for Automated View Classification of Pediatric Focused Assessment With Sonography for Trauma.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVE: Pediatric focused assessment with sonography for trauma (FAST) is a sequence of ultrasound views rapidly performed by clinicians to diagnose hemorrhage. A technical limitation of FAST is the lack of expertise to consistently acquire all re...

Improving Sensitivity of Arterial Spin Labeling Perfusion MRI in Alzheimer's Disease Using Transfer Learning of Deep Learning-Based ASL Denoising.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are m...