AIMC Topic: Multicenter Studies as Topic
Clear Filters Showing 61 to 70 of 75 articles
Renal impairment and outcome in patients with takotsubo cardiomyopathy.
The American journal of emergency medicine
Dec 23, 2015
OBJECTIVES: The objectives were to ascertain the prevalence of renal impairment among patients with a takotsubo cardiomyopathy (TTC) episode and whether clinical outcomes are related to renal function.
Establishing a multi-institutional registry to compare the outcomes of robotic, laparoscopic, and open surgery for gastric cancer.
Surgery
Jan 26, 2015
Update on the detection of frailty in older adults: a multicenter cohort machine learning-based study protocol.
Aging
May 21, 2025
BACKGROUND: This study aims to investigate the relationship between muscle activation variables assessed via ultrasound and the comprehensive assessment of geriatric patients, as well as to analyze ultrasound images to determine their correlation wit...
Triple cardiovascular disease detection with an artificial intelligence-enabled stethoscope (TRICORDER): design and rationale for a decentralised, real-world cluster-randomised controlled trial and implementation study.
BMJ open
May 21, 2025
INTRODUCTION: Early detection of cardiovascular disease in primary care is a public health priority, for which the clinical and cost-effectiveness of an artificial intelligence-enabled stethoscope that detects left ventricular systolic dysfunction, a...
A Semi-Automated Approach Based on Network Analysis to Suggest New Collaborations and Foster Multisite Clinical Trials.
Studies in health technology and informatics
May 15, 2025
Several research institutions nowadays collaboratively conduct many scientific projects. Within a national Italian initiative on robotic rehabilitation, this study aims to develop new collaborations that can support the project's missions. Bibliograp...
Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH.
Journal of hepatology
May 1, 2025
BACKGROUND & AIMS: Intra and inter-pathologist variability poses a significant challenge in metabolic dysfunction-associated steatohepatitis (MASH) biopsy evaluation, leading to suboptimal selection of patients and confounded assessment of histologic...
AUGUR-AIM: Clinical validation of an artificial intelligence indocyanine green fluorescence angiography expert representer.
Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
Apr 1, 2025
AIM: Recent randomized controlled trials and meta-analyses have demonstrated a reduction in the anastomotic leak rate when indocyanine green fluorescence angiography (ICGFA) is used versus when it is not in colorectal resections. We have previously d...
Insight into deep learning for glioma IDH medical image analysis: A systematic review.
Medicine
Feb 16, 2024
BACKGROUND: Deep learning techniques explain the enormous potential of medical image analysis, particularly in digital pathology. Concurrently, molecular markers have gained increasing significance over the past decade in the context of glioma patien...
A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.
Radiology. Artificial intelligence
Jan 1, 2024
Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation of cardiac MRI data from a multicenter registry of patients with Fontan circulation (Fontan Outcomes Registry Using CMR Examinations [FORCE]). Materia...
Deep Learning-based Identification of Brain MRI Sequences Using a Model Trained on Large Multicentric Study Cohorts.
Radiology. Artificial intelligence
Jan 1, 2024
Purpose To develop a fully automated device- and sequence-independent convolutional neural network (CNN) for reliable and high-throughput labeling of heterogeneous, unstructured MRI data. Materials and Methods Retrospective, multicentric brain MRI da...
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