AIMC Topic: Automation

Clear Filters Showing 581 to 590 of 967 articles

Automatic segmentation of hyperreflective foci in OCT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The leading cause of vision loss in the Western World is Age-related Macular Degeneration (AMD), but together with modern medicines, tracking the number of Hyperreflective Foci (HF) on Optical Coherence Tomography (OCT) imag...

AutoCryoPicker: an unsupervised learning approach for fully automated single particle picking in Cryo-EM images.

BMC bioinformatics
BACKGROUND: An important task of macromolecular structure determination by cryo-electron microscopy (cryo-EM) is the identification of single particles in micrographs (particle picking). Due to the necessity of human involvement in the process, curre...

Fully Automated Segmentation of Lower Extremity Deep Vein Thrombosis Using Convolutional Neural Network.

BioMed research international
OBJECTIVE: Deep vein thrombosis (DVT) is a disease caused by abnormal blood clots in deep veins. Accurate segmentation of DVT is important to facilitate the diagnosis and treatment. In the current study, we proposed a fully automatic method of DVT de...

Deep-Learning Language-Modeling Approach for Automated, Personalized, and Iterative Radiology-Pathology Correlation.

Journal of the American College of Radiology : JACR
PURPOSE: Radiology-pathology correlation has long been foundational to continuing education, peer learning, quality assurance, and multidisciplinary patient care. The objective of this study was to determine whether modern deep-learning language-mode...

IILS: Intelligent imaging layout system for automatic imaging report standardization and intra-interdisciplinary clinical workflow optimization.

EBioMedicine
BACKGROUND: To achieve imaging report standardization and improve the quality and efficiency of the intra-interdisciplinary clinical workflow, we proposed an intelligent imaging layout system (IILS) for a clinical decision support system-based ubiqui...

Learning-based automatic segmentation of arteriovenous malformations on contrast CT images in brain stereotactic radiosurgery.

Medical physics
PURPOSE: Stereotactic radiosurgery (SRS) is widely used to obliterate arteriovenous malformations (AVMs). Its performance relies on the accuracy of delineating the target AVM. Manual segmentation during a framed SRS procedure is time consuming and su...

Automating Ischemic Stroke Subtype Classification Using Machine Learning and Natural Language Processing.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: The manual adjudication of disease classification is time-consuming, error-prone, and limits scaling to large datasets. In ischemic stroke (IS), subtype classification is critical for management and outcome prediction. This study sought to...

Predicting Reaction Products and Automating Reactive Trajectory Characterization in Molecular Simulations with Support Vector Machines.

Journal of chemical information and modeling
A machine learning-based methodology for the prediction of chemical reaction products, along with automated elucidation of mechanistic details via phase space analysis of reactive trajectories, is introduced using low-dimensional heuristic models and...