AIMC Topic: Middle Aged

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Machine learning based outcome prediction of large vessel occlusion of the anterior circulation prior to thrombectomy in patients with wake-up stroke.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
PURPOSE: Outcome prediction of large vessel occlusion of the anterior circulation in patients with wake-up stroke is important to identify patients that will benefit from thrombectomy. Currently, mismatch concepts that require MRI or CT-Perfusion (CT...

Deep Learning Reconstruction for Accelerated Spine MRI: Prospective Analysis of Interchangeability.

Radiology
Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To...

Exactech Equinoxe anatomic versus reverse total shoulder arthroplasty for primary osteoarthritis: case controlled comparisons using the machine learning-derived Shoulder Arthroplasty Smart score.

Journal of shoulder and elbow surgery
BACKGROUND: The role of reverse total shoulder arthroplasty (rTSA) for glenohumeral osteoarthritis (GHOA) with an intact rotator cuff remains unclear with prior investigations demonstrating similar patient-reported outcome measures (PROMs) to anatomi...

Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI.

European radiology
OBJECTIVES: Time-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation (VCD) is required to achieve reliable results. We sought to evaluate manual analysis (MA) compared to ...

Deep Learning for Estimating Lung Capacity on Chest Radiographs Predicts Survival in Idiopathic Pulmonary Fibrosis.

Radiology
Background Total lung capacity (TLC) has been estimated with use of chest radiographs based on time-consuming methods, such as planimetric techniques and manual measurements. Purpose To develop a deep learning-based, multidimensional model capable of...

Virtual Biopsy by Using Artificial Intelligence-based Multimodal Modeling of Binational Mammography Data.

Radiology
Background Computational models based on artificial intelligence (AI) are increasingly used to diagnose malignant breast lesions. However, assessment from radiologic images of the specific pathologic lesion subtypes, as detailed in the results of bio...

Surgical cost of robotic-assisted sacrocolpopexy: a comparison of two robotic platforms.

International urogynecology journal
IMPORTANCE: Robotic assistance in pelvic organ prolapse surgery can improve surgeon ergonomics and instrument dexterity compared with traditional laparoscopy but at increased costs.

Robotic cochlear implantation in post-meningitis ossified cochlea.

American journal of otolaryngology
AIM: To report the experience of an image-guided and navigation-based robot arm as an assistive surgical tool for cochlear implantation in a case with a labyrinthitis ossificans.

An artificial-intelligence-based age-specific template construction framework for brain structural analysis using magnetic resonance images.

Human brain mapping
It is an essential task to construct brain templates and analyze their anatomical structures in neurological and cognitive science. Generally, templates constructed from magnetic resonance imaging (MRI) of a group of subjects can provide a standard r...

Brain Age Prediction: A Comparison between Machine Learning Models Using Brain Morphometric Data.

Sensors (Basel, Switzerland)
Brain structural morphology varies over the aging trajectory, and the prediction of a person's age using brain morphological features can help the detection of an abnormal aging process. Neuroimaging-based brain age is widely used to quantify an indi...