AIMC Topic: Automation
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Hybrid clinical-radiomics model based on fully automatic segmentation for predicting the early expansion of spontaneous intracerebral hemorrhage: A multi-center study.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 31, 2024
BACKGROUND: Early prediction of hematoma expansion (HE) is important for the development of therapeutic strategies for spontaneous intracerebral hemorrhage (sICH). Radiomics can help to predict early hematoma expansion in intracerebral hemorrhage. Ho...
Cerebral Hemorrhage
Risk Factors
Retrospective Studies
Aged
Predictive Value of Tests
Tomography, X-Ray Computed
Automation
Aged, 80 and over
Radiographic Image Interpretation, Computer-Assisted
Female
Male
Radiomics
Hematoma
Reproducibility of Results
Deep Learning
Middle Aged
Humans
China
Risk Assessment
Decision Support Techniques
Time Factors
Disease Progression
Prognosis
Nomograms
Improvement of bioanalytical parameters through automation: suitability of a hand-like robotic system.
Analytical and bioanalytical chemistry
Aug 29, 2024
Commercial automation systems for small- and medium-sized laboratories, including research environments, are often complex to use. For liquid handling systems (LHS), development is required not only for the robot's movements but also for adapting the...
An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading.
JACC. Cardiovascular imaging
Aug 14, 2024
BACKGROUND: Considering the high prevalence of mitral regurgitation (MR) and the highly subjective, variable MR severity reporting, an automated tool that could screen patients for clinically significant MR (≥ moderate) would streamline the diagnosti...
Automatic localization of anatomical landmarks in head cine fluoroscopy images via deep learning.
Medical physics
Aug 14, 2024
BACKGROUND: Fluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; personalized patient dosimetry is necessary to improve patient safety during these procedures. However, current FGIs systems do not capture the precise e...
Automatic deep learning segmentation of the hippocampus on high-resolution diffusion magnetic resonance imaging and its application to the healthy lifespan.
NMR in biomedicine
Aug 13, 2024
Diffusion tensor imaging (DTI) can provide unique contrast and insight into microstructural changes with age or disease of the hippocampus, although it is difficult to measure the hippocampus because of its comparatively small size, location, and sha...
Smart parallel automated cryo-electron tomography.
Nature methods
Aug 8, 2024
In situ cryo-electron tomography enables investigation of macromolecules in their native cellular environment. Samples have become more readily available owing to recent software and hardware advancements. Data collection, however, still requires an ...
AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases.
Nature medicine
Aug 7, 2024
Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalcoholic steatohepatitis) require histologic scoring for assessment of inclusion criteria and endpoints. However, variability in interpretation has impac...
Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values.
NMR in biomedicine
Aug 4, 2024
Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnormalities, and it provides baseline tissue characterization. Post-contrast T1 mapping enhances tissue differentiation, enables extracellular volume (ECV...
Automated segmentation in pelvic radiotherapy: A comprehensive evaluation of ATLAS-, machine learning-, and deep learning-based models.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Aug 3, 2024
Artificial intelligence can standardize and automatize highly demanding procedures, such as manual segmentation, especially in an anatomical site as common as the pelvis. This study investigated four automated segmentation tools on computed tomograph...
Clinical implementation and evaluation of deep learning-assisted automatic radiotherapy treatment planning for lung cancer.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Aug 2, 2024
PURPOSE: The purpose of the study is to investigate the clinical application of deep learning (DL)-assisted automatic radiotherapy planning for lung cancer.
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