AIMC Topic: Prospective Studies

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A Comparison of Natural Language Processing Methods for the Classification of Lumbar Spine Imaging Findings Related to Lower Back Pain.

Academic radiology
RATIONALE AND OBJECTIVES: The use of natural language processing (NLP) in radiology provides an opportunity to assist clinicians with phenotyping patients. However, the performance and generalizability of NLP across healthcare systems is uncertain. W...

Deep Learning Image Processing Enables 40% Faster Spinal MR Scans Which Match or Exceed Quality of Standard of Care : A Prospective Multicenter Multireader Study.

Clinical neuroradiology
OBJECTIVE: This prospective multicenter multireader study evaluated the performance of 40% scan-time reduced spinal magnetic resonance imaging (MRI) reconstructed with deep learning (DL).

Comparison of the short-term efficacy of two types of robotic total mesorectal excision for rectal cancer.

Techniques in coloproctology
BACKGROUND: The advantages and disadvantages of robotic technology compared with conventional surgery for low rectal cancer have been discussed extensively. However, a few studies on the efficacy of total mesorectal excision (TME) with different robo...

Unsupervised Learning for Automated Detection of Coronary Artery Disease Subgroups.

Journal of the American Heart Association
Background The promise of precision population health includes the ability to use robust patient data to tailor prevention and care to specific groups. Advanced analytics may allow for automated detection of clinically informative subgroups that acco...

Deep neural network for video colonoscopy of ulcerative colitis: a cross-sectional study.

The lancet. Gastroenterology & hepatology
BACKGROUND: A combination of endoscopic and histological evaluation is important in the management of patients with ulcerative colitis. We aimed to adapt our previous deep neural network system (deep neural ulcerative colitis [DNUC]) to full video co...

Deep Learning Enables 60% Accelerated Volumetric Brain MRI While Preserving Quantitative Performance: A Prospective, Multicenter, Multireader Trial.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: In this prospective, multicenter, multireader study, we evaluated the impact on both image quality and quantitative image-analysis consistency of 60% accelerated volumetric MR imaging sequences processed with a commercially av...

Implementation and prospective clinical validation of AI-based planning and shimming techniques in cardiac MRI.

Medical physics
PURPOSE: Cardiovascular magnetic resonance (CMR) is a vital diagnostic tool in the management of cardiovascular diseases. The advent of advanced CMR technologies combined with artificial intelligence (AI) has the potential to simplify imaging, reduce...

Simplified PADUA renal (SPARE) nephrometry score validation and long-term outcomes after robot-assisted partial nephrectomy.

Urologic oncology
BACKGROUND: International guidelines suggest the use of anatomic scores to predict surgical outcomes after partial nephrectomy (PN). We aimed at validating the use of Simplified PADUA Renal (SPARE) nephrometry score in robot-assisted PN (RAPN).

Radiation dose reduction with deep-learning image reconstruction for coronary computed tomography angiography.

European radiology
OBJECTIVES: Deep-learning image reconstruction (DLIR) offers unique opportunities for reducing image noise without degrading image quality or diagnostic accuracy in coronary CT angiography (CCTA). The present study aimed at exploiting the capabilitie...