AIMC Topic: Prospective Studies
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Robot-assisted Versus Open Radical Cystectomy in Bladder Cancer: An Economic Evaluation Alongside a Multicentre Comparative Effectiveness Study.
European urology focus
Jun 24, 2021
BACKGROUND: Open radical cystectomy (ORC) is regarded as the standard treatment for muscle-invasive bladder cancer, but robot-assisted radical cystectomy (RARC) is increasingly used in practice. A recent study showed that RARC resulted in slightly fe...
Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study.
PloS one
Jun 24, 2021
BACKGROUND: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values ca...
Robot-assisted sacrocolpopexy: not only for vaginal vault suspension? An observational cohort study.
International urogynecology journal
Jun 23, 2021
INTRODUCTION AND HYPOTHESIS: Surgery for pelvic organ prolapse (POP) has high recurrence rates. Long-term anatomical and patient-reported outcomes after pelvic floor repair are therefore required.
Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study.
Journal of medical Internet research
Jun 21, 2021
BACKGROUND: The Multidimensional Prognostic Index (MPI) is an aggregate, comprehensive, geriatric assessment scoring system derived from eight domains that predict adverse outcomes, including 12-month mortality. However, the prediction accuracy of us...
The successful implementation of the Navio robotic technology required 29 cases.
Journal of robotic surgery
Jun 19, 2021
Robotic-assisted total knee arthroplasty (RA-TKA) has potential benefits of improved restoration of mechanical alignment, accuracy of bony resection, and balancing. The purpose of this study was to determine the number of cases necessary for a single...
Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).
Scientific reports
Jun 17, 2021
In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocation, timely management, and possibly, outcome. The study objective is to develop and validate individu...
Performance evaluation of a deep learning image reconstruction (DLIR) algorithm in "double low" chest CTA in children: a feasibility study.
La Radiologia medica
Jun 16, 2021
BACKGROUND: Chest CT angiography (CTA) is a convenient clinical examination for children with an increasing need to reduce both radiation and contrast medium doses. Iterative Reconstruction algorithms are often used to reduce image noise but encounte...
Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration.
European radiology
Jun 15, 2021
OBJECTIVES: To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep learning image reconstruction (DLIR) and compare them with those of images rec...
Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.
Nature biomedical engineering
Jun 15, 2021
Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidn...
Metadata
Photography
Body Weight
Retina
Body Height
Image Interpretation, Computer-Assisted
Blood Glucose
ROC Curve
Diabetes Mellitus, Type 2
Renal Insufficiency, Chronic
Humans
Male
Glomerular Filtration Rate
Neural Networks, Computer
Middle Aged
Body Mass Index
Prospective Studies
Disease Progression
Area Under Curve
Female
Fundus Oculi
Deep Learning
Deep Learning to Predict Cardiac Magnetic Resonance-Derived Left Ventricular Mass and Hypertrophy From 12-Lead ECGs.
Circulation. Cardiovascular imaging
Jun 15, 2021
BACKGROUND: Classical methods for detecting left ventricular (LV) hypertrophy (LVH) using 12-lead ECGs are insensitive. Deep learning models using ECG to infer cardiac magnetic resonance (CMR)-derived LV mass may improve LVH detection.
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