AIMC Topic: Retrospective Studies

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Machine Learning-Based Prediction of Delayed Neurologic Sequelae in Carbon Monoxide Poisoning Using Automatically Extracted MR Imaging Features.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Delayed neurologic sequelae are among the most serious complications of carbon monoxide poisoning. However, no reliable tools are available for evaluating their potential risk. We aimed to assess whether machine learning model...

Evaluation of artificial-intelligence-based liver segmentation and its application for longitudinal liver volume measurement.

Abdominal radiology (New York)
BACKGROUND: Accurate liver-volume measurements from CT scans are essential for treatment planning, particularly in liver resection cases, to avoid postoperative liver failure. However, manual segmentation is time-consuming and prone to variability. A...

Arthroscopy-validated diagnostic performance of sub-5-min deep learning super-resolution 3T knee MRI in children and adolescents.

Skeletal radiology
OBJECTIVE: This study aims to determine the diagnostic performance of sub-5-min combined sixfold parallel imaging (PIx3)-simultaneous multislice (SMSx2)-accelerated deep learning (DL) super-resolution 3T knee MRI in children and adolescents.

Improved Breast Cancer Detection with Artificial Intelligence in a Real-World Digital Breast Tomosynthesis Screening Program.

Clinical breast cancer
OBJECTIVE: The purpose of this study is to compare radiologists' breast cancer screening performance before and after the implementation of an artificial intelligence (AI) detection system for digital breast tomosynthesis (DBT).

Artificial intelligence-enhanced electrocardiogram diastolic function grade predicts post-septal myectomy mortality in hypertrophic cardiomyopathy.

The Journal of thoracic and cardiovascular surgery
BACKGROUNDS: Diastolic dysfunction is an important pathophysiologic feature of hypertrophic cardiomyopathy that is often challenging to determine noninvasively. This study investigated whether a novel artificial intelligence-enabled electrocardiograp...

Using AI to triage patients without clinically significant prostate cancer using biparametric MRI and PSA.

Abdominal radiology (New York)
OBJECTIVES: To train and evaluate the performance of a machine learning triaging tool that identifies MRI negative for clinically significant prostate cancer and to compare this against non-MRI models.

Rate- and Patient-Specific Risk Factors for Periprosthetic Acetabular Fractures During Primary Total Hip Arthroplasty Using a Press-Fit Cup.

The Journal of arthroplasty
BACKGROUND: Periprosthetic acetabular fractures following primary total hip arthroplasty (THA) using a cementless acetabular component range from occult to severe fractures. The aims of this study were to evaluate the perioperative periprosthetic ace...

End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study.

European radiology
OBJECTIVES: Pancreatic cancer treatment plans involving surgery and/or chemotherapy are highly dependent on disease stage. However, current staging systems are ineffective and poorly correlated with survival outcomes. We investigate how artificial in...