AIMC Topic: Feasibility Studies
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Clinical feasibility of deep learning reconstruction in liver diffusion-weighted imaging: Improvement of image quality and impact on apparent diffusion coefficient value.
European journal of radiology
Oct 13, 2023
PURPOSE: Diffusion-weighted imaging (DWI) of the liver suffers from low resolution, noise, and artifacts. This study aimed to investigate the effect of deep learning reconstruction (DLR) on image quality and apparent diffusion coefficient (ADC) quant...
ChatGPT and the Future of Journal Reviews: A Feasibility Study.
The Yale journal of biology and medicine
Sep 29, 2023
The increasing volume of research submissions to academic journals poses a significant challenge for traditional peer-review processes. To address this issue, this study explores the potential of employing ChatGPT, an advanced large language model (L...
A Cadaveric Feasibility Study of an Automatic Multi-Degrees of Freedom Surgical Robot for Percutaneous Scaphoid Guide Pin Insertion.
The journal of hand surgery Asian-Pacific volume
Sep 25, 2023
Percutaneous fixation of scaphoid fractures need accurate guide pin insertion. The emergence of computer-assisted navigation and robotic surgery may provide a promising solution to this problem. This study presents the development of an automatic m...
Coronary computed tomography angiographic detection of in-stent restenosis via deep learning reconstruction: a feasibility study.
European radiology
Sep 6, 2023
OBJECTIVES: Evaluation of in-stent restenosis (ISR), especially for small stents, remains challenging during computed tomography (CT) angiography. We used deep learning reconstruction to quantify stent strut thickness and lumen vessel diameter at the...
Safety and feasibility of single-port surgery for posterior retroperitoneal adrenalectomy using the da Vinci SP robotic system: a retrospective cohort study.
Surgical endoscopy
Sep 6, 2023
BACKGROUND: This study demonstrates our experience of single-port robotic posterior retroperitoneal adrenalectomy (RPRA) using the da Vinci SP robot system and evaluates its technical feasibility and surgical outcomes.
Robot-assisted PSMA-radioguided Surgery to Assess Surgical Margins and Nodal Metastases in Prostate Cancer Patients: Report on Three Cases Using an Intraoperative PET-CT Specimen Imager.
Urology
Sep 3, 2023
INTRODUCTION: The aim of this feasibility study was to test the intraoperative use of this brand-new specimen PET/CT to guide robot-assisted radical prostatectomy and pelvic lymph node dissection.
Feasibility of the set-up for the different approaches in robotic head and neck surgery with the Versius Surgical System.
Journal of robotic surgery
Aug 23, 2023
The Versius Surgical System is a next generation soft-tissue robot with instrument and endoscope arms split into individual modules. Despite its similarities with previous systems, the basic changes in the design raise concerns relating to the feasib...
Robotic locomotor training in a low-resource setting: a randomized pilot and feasibility trial.
Disability and rehabilitation
Aug 22, 2023
PURPOSE: Activity-based Training (ABT) represents the current standard of neurological rehabilitation. Robotic Locomotor Training (RLT), an innovative technique, aims to enhance rehabilitation outcomes. This study aimed to conduct a randomized pilot ...
Clinical trial protocol for P-NeLoP: a randomized controlled trial comparing the feasibility and outcomes of robot-assisted partial nephrectomy with low insufflation pressure using AirSeal versus standard insufflation pressure (UroCCR no. 85 study).
Trials
Aug 19, 2023
Robot-assisted partial nephrectomy (RAPN) is the standard of care for small, localized kidney tumors. This surgery is conducted within a short hospital stay and can even be performed as outpatient surgery in selected patients. In order to allow early...
Federated Learning: A Cross-Institutional Feasibility Study of Deep Learning Based Intracranial Tumor Delineation Framework for Stereotactic Radiosurgery.
Journal of magnetic resonance imaging : JMRI
Aug 12, 2023
BACKGROUND: Deep learning-based segmentation algorithms usually required large or multi-institute data sets to improve the performance and ability of generalization. However, protecting patient privacy is a key concern in the multi-institutional stud...
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