AIMC Topic: Prospective Studies

Clear Filters Showing 951 to 960 of 2403 articles

Feature Tracking and Segmentation in Real Time via Deep Learning in Vitreoretinal Surgery: A Platform for Artificial Intelligence-Mediated Surgical Guidance.

Ophthalmology. Retina
PURPOSE: This study investigated whether a deep-learning neural network can detect and segment surgical instrumentation and relevant tissue boundaries and landmarks within the retina using imaging acquired from a surgical microscope in real time, wit...

Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network.

Acta dermato-venereologica
Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with...

Efficacy and Safety of Robot-assisted AUS Implantation Surgery in Treating Severe Stress Urinary Incontinence: A Systematic Review and Meta-Analysis.

Urology
OBJECTIVE: To investigate the effectiveness and safety of robot-assisted artificial urinary sphincter (AUS) implantation surgery for female patients with severe stress urinary incontinences (SUI) by performing a systematic literature review.

Machine Learning-Enabled Fully Automated Assessment of Left Ventricular Volume, Ejection Fraction and Strain: Experience in Pediatric and Young Adult Echocardiography.

Pediatric cardiology
BACKGROUND: Left ventricular (LV) volumes, ejection fraction (EF), and myocardial strain have been shown to be predictive of clinical and subclinical heart disease. Automation of LV functional assessment overcomes difficult technical challenges and c...

Systematic analysis of the test design and performance of AI/ML-based medical devices approved for triage/detection/diagnosis in the USA and Japan.

Scientific reports
The development of computer-aided detection (CAD) using artificial intelligence (AI) and machine learning (ML) is rapidly evolving. Submission of AI/ML-based CAD devices for regulatory approval requires information about clinical trial design and per...

Space-time-regulated imaging analyzer for smart coagulation diagnosis.

Cell reports. Medicine
The development of intelligent blood coagulation diagnoses is awaited to meet the current need for large clinical time-sensitive caseloads due to its efficient and automated diagnoses. Herein, a method is reported and validated to realize it through ...

Good view frames from ultrasonography (USG) video containing ONS diameter using state-of-the-art deep learning architectures.

Medical & biological engineering & computing
This paper presents an automated method for detection of the diagnostically prominent frames containing optic nerve sheath (ONS) from ocular ultrasonography video using deep learning; such frames are referred to as "Good View" frames in this paper. V...

Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study.

BMC bioinformatics
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have resulted in significant enthusiasm for their promise in healthcare. Despite this, prospective randomized controlled trials and successful clinical implementation remain limited. ...

Application of deep learning-based image reconstruction in MR imaging of the shoulder joint to improve image quality and reduce scan time.

European radiology
OBJECTIVES: To compare the image quality and diagnostic performance of conventional motion-corrected periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) MRI sequences with post-processed PROPELLER MRI sequences usi...