AIMC Topic: Retrospective Studies

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Deep learning-accelerated image reconstruction in back pain-MRI imaging: reduction of acquisition time and improvement of image quality.

La Radiologia medica
INTRODUCTION: Low back pain is a global health issue causing disability and missed work days. Commonly used MRI scans including T1-weighted and T2-weighted images provide detailed information of the spine and surrounding tissues. Artificial intellige...

Single-Port Multiport Robot-Assisted Partial Nephrectomy: A Meta-Analysis.

Journal of endourology
Several centers have reported their experience with single-port robot-assisted partial nephrectomy (SP-RAPN); however, it is uncertain if utilization of this platform represents an improvement in outcomes compared to multiport robot-assisted partial...

Machine Learning Methods as a Cost-Effective Alternative to Physics-Based Binding Free Energy Calculations.

Molecules (Basel, Switzerland)
The rank ordering of ligands remains one of the most attractive challenges in drug discovery. While physics-based in silico binding affinity methods dominate the field, they still have problems, which largely revolve around forcefield accuracy and sa...

Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.

Internal medicine (Tokyo, Japan)
Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myocardial fibrosis and extracellular volume (ECV) of the left ventricular myocardium (LVM), a similar evaluation has recently become possible using comp...

Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.

American journal of ophthalmology
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...

Identifying Pathological Subtypes of Brain Metastasis from Lung Cancer Using MRI-Based Deep Learning Approach: A Multicenter Study.

Journal of imaging informatics in medicine
The aim of this study was to investigate the feasibility of deep learning (DL) based on multiparametric MRI to differentiate the pathological subtypes of brain metastasis (BM) in lung cancer patients. This retrospective analysis collected 246 patient...

Artificial Intelligence-Guided Segmentation and Path Planning Software for Transthoracic Lung Biopsy.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To validate the sensitivity and specificity of a 3-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) software for lung lesion detection and to establish concordance between AI-generated needle paths and those u...

A supervised machine learning model for identifying predictive factors for recommending head and neck cancer surgery.

Head & neck
BACKGROUND: New patient referrals are often processed by practice coordinators with little-to-no medical background. Treatment delays due to incorrect referral processing, however, have detrimental consequences. Identifying variables that are associa...