AIMC Topic: Workflow
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Assisted phase and step annotation for surgical videos.
International journal of computer assisted radiology and surgery
Feb 10, 2020
PURPOSE: Annotation of surgical videos is a time-consuming task which requires specific knowledge. In this paper, we present and evaluate a deep learning-based method that includes pre-annotation of the phases and steps in surgical videos and user as...
From Data to Value: How Artificial Intelligence Augments the Radiology Business to Create Value.
Seminars in musculoskeletal radiology
Jan 28, 2020
The radiology practice has access to a wealth of data in the radiologist information system, dictation reports, and electronic health records. Although many artificial intelligence applications in radiology have focused on computer vision and the int...
The Emerging Role of Radiomics in COPD and Lung Cancer.
Respiration; international review of thoracic diseases
Jan 28, 2020
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineab...
Convolutional neural network-automated hepatobiliary phase adequacy evaluation may optimize examination time.
European journal of radiology
Jan 14, 2020
PURPOSE: To develop and evaluate the performance of a fully-automated convolutional neural network (CNN)-based algorithm to evaluate hepatobiliary phase (HBP) adequacy of gadoxetate disodium (EOB)-enhanced MRI. Secondarily, we explored the potential ...
Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data.
Nature protocols
Jan 13, 2020
DNA methylation data-based precision cancer diagnostics is emerging as the state of the art for molecular tumor classification. Standards for choosing statistical methods with regard to well-calibrated probability estimates for these typically highly...
Deep learning for detecting retinal detachment and discerning macular status using ultra-widefield fundus images.
Communications biology
Jan 8, 2020
Retinal detachment can lead to severe visual loss if not treated timely. The early diagnosis of retinal detachment can improve the rate of successful reattachment and the visual results, especially before macular involvement. Manual retinal detachmen...
Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data.
Communications biology
Jan 7, 2020
Single-molecule research techniques such as patch-clamp electrophysiology deliver unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysi...
Knowledge Base Commons (KBCommons) v1.1: a universal framework for multi-omics data integration and biological discoveries.
BMC genomics
Dec 20, 2019
BACKGROUND: Knowledge Base Commons (KBCommons) v1.1 is a universal and all-inclusive web-based framework providing generic functionalities for storing, sharing, analyzing, exploring, integrating and visualizing multiple organisms' genomics and integr...
Application of automated electron microscopy imaging and machine learning to characterise and quantify nanoparticle dispersion in aqueous media.
Journal of microscopy
Dec 18, 2019
For many nanoparticle applications it is important to understand dispersion in liquids. For nanomedicinal and nanotoxicological research this is complicated by the often complex nature of the biological dispersant and ultimately this leads to severe ...
Artificial intelligence in diagnostic imaging: impact on the radiography profession.
The British journal of radiology
Dec 16, 2019
The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radio...
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