AIMC Topic: Workflow
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Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds.
Molecules (Basel, Switzerland)
Dec 13, 2020
Permeation through the blood-brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence num...
Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation.
Journal of vascular surgery
Dec 9, 2020
OBJECTIVE: Imaging software has become critical tools in the diagnosis and decision making for the treatment of abdominal aortic aneurysms (AAA). However, the interobserver reproducibility of the maximum cross-section diameter is poor. This study aim...
Humans
Aortography
Radiographic Image Interpretation, Computer-Assisted
Predictive Value of Tests
Workflow
Aortic Aneurysm, Abdominal
Computed Tomography Angiography
Retrospective Studies
Automation
Observer Variation
Anatomic Landmarks
Software Design
Reproducibility of Results
Multidetector Computed Tomography
Deep Learning
A Workflow for the Performance of the Differential Ovarian Follicle Count Using Deep Neuronal Networks.
Toxicologic pathology
Dec 8, 2020
In order to automate the counting of ovarian follicles required in multigeneration reproductive studies performed in the rat according to Organization for Economic Co-operation and Development guidelines 443 and 416, the application of deep neural ne...
Use of Machine Learning to Improve Echocardiographic Image Interpretation Workflow: A Disruptive Paradigm Change?
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Dec 1, 2020
Fully‑automated deep‑learning segmentation of pediatric cardiovascular magnetic resonance of patients with complex congenital heart diseases.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Nov 30, 2020
BACKGROUND: For the growing patient population with congenital heart disease (CHD), improving clinical workflow, accuracy of diagnosis, and efficiency of analyses are considered unmet clinical needs. Cardiovascular magnetic resonance (CMR) imaging of...
Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study.
EBioMedicine
Nov 27, 2020
BACKGROUND: We aimed to develop and validate a real-time deep convolutional neural networks (DCNNs) system for detecting early gastric cancer (EGC).
A random forest based biomarker discovery and power analysis framework for diagnostics research.
BMC medical genomics
Nov 23, 2020
BACKGROUND: Biomarker identification is one of the major and important goal of functional genomics and translational medicine studies. Large scale -omics data are increasingly being accumulated and can provide vital means for the identification of bi...
Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation.
European radiology
Nov 21, 2020
OBJECTIVE: The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we ...
A data driven methodology for social science research with left-behind children as a case study.
PloS one
Nov 20, 2020
For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research ...
Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study.
Journal of medical Internet research
Nov 19, 2020
BACKGROUND: Machine learning models have the potential to improve diagnostic accuracy and management of acute conditions. Despite growing efforts to evaluate and validate such models, little is known about how to best translate and implement these pr...
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