Hospital-Based Medicine

Risk Management

Latest AI and machine learning research in risk management for healthcare professionals.

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Assessment of artificial intelligence (AI) reporting methodology in glioma MRI studies using the Checklist for AI in Medical Imaging (CLAIM).

PURPOSE: The Checklist for Artificial Intelligence in Medical Imaging (CLAIM) is a recently released...

A Novel Tactile Function Assessment Using a Miniature Tactile Stimulator.

Several methods for the measurement of tactile acuity have been devised previously, but unexpected n...

Cross Dataset Analysis for Generalizability of HRV-Based Stress Detection Models.

Stress is an increasingly prevalent mental health condition across the world. In Europe, for example...

Role of artificial intelligence-guided esophagogastroduodenoscopy in assessing the procedural completeness and quality.

BACKGROUND AND AIMS: The quality of esophagogastroduodenoscopy (EGD) can have great impact on the de...

A practical guide to deep-learning light-field microscopy for 3D imaging of biological dynamics.

Here, we present a step-by-step protocol for the implementation of deep-learning-enhanced light-fiel...

dtiRIM: A generalisable deep learning method for diffusion tensor imaging.

Diffusion weighted MRI is an indispensable tool for routine patient screening and diagnostics of pat...

Artificial intelligence in medicine - is too much transparency a good thing?

Some encouraging uses for AI in medicine will lead to potentially novel legal liability issues. Comp...

Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI.

Background MRI is a powerful diagnostic tool with a long acquisition time. Recently, deep learning (...

The effect of machine learning tools for evidence synthesis on resource use and time-to-completion: protocol for a retrospective pilot study.

BACKGROUND: Machine learning (ML) tools exist that can reduce or replace human activities in repetit...

Accuracy of Advanced Active Robot for Total Knee Arthroplasty: A Cadaveric Study.

Although the accuracy of other types of robotic systems for total knee arthroplasty (TKA) has been a...

Four-Dimensional Printing of Stimuli-Responsive Hydrogel-Based Soft Robots.

The present protocol describes the creation of four-dimensional (4D), time-dependent, shape-changeab...

Rapid lumbar MRI protocol using 3D imaging and deep learning reconstruction.

BACKGROUND AND PURPOSE: Three-dimensional (3D) imaging of the spine, augmented with AI-enabled image...

Evaluation of deep-learning image reconstruction for chest CT examinations at two different dose levels.

AIMS: The aims of the present study were to, for both a full-dose protocol and an ultra-low dose (UL...

Technical performance of a dual-energy CT system with a novel deep-learning based reconstruction process: Evaluation using an abdomen protocol.

BACKGROUND: A new tube voltage-switching dual-energy (DE) CT system using a novel deep-learning base...

Same-Day Discharge After Robot-Assisted Partial Nephrectomy: Is It Worth It?

Robot-assisted partial nephrectomy (RAPN) has traditionally been performed as an inpatient procedur...

Artificial Intelligence in Breast X-Ray Imaging.

This topical review is focused on the clinical breast x-ray imaging applications of the rapidly evol...

An Artificial Intelligence Tool for Clinical Decision Support and Protocol Selection for Brain MRI.

BACKGROUND AND PURPOSE: Protocolling, the process of determining the most appropriate acquisition pa...

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