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Workflow

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Extracting Rectified Building Footprints from Traditional Orthophotos: A New Workflow.

Sensors (Basel, Switzerland)
Deep learning techniques such as convolutional neural networks have largely improved the performance of building segmentation from remote sensing images. However, the images for building segmentation are often in the form of traditional orthophotos, ...

An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology.

Medical & biological engineering & computing
Physics-based analyses have the potential to consolidate and substantiate medical diagnoses in rhinology. Such methods are frequently subject to intense investigations in research. However, they are not used in clinical applications, yet. One issue p...

Image-Based Artificial Intelligence in Wound Assessment: A Systematic Review.

Advances in wound care
Accurately predicting wound healing trajectories is difficult for wound care clinicians due to the complex and dynamic processes involved in wound healing. Wound care teams capture images of wounds during clinical visits generating big datasets over...

Mitigating Cold Start Problem in Serverless Computing with Function Fusion.

Sensors (Basel, Switzerland)
As Artificial Intelligence (AI) is becoming ubiquitous in many applications, serverless computing is also emerging as a building block for developing cloud-based AI services. Serverless computing has received much interest because of its simplicity, ...

Automation of a Rule-based Workflow to Estimate Age from Brain MR Imaging of Infants and Children Up to 2 Years Old Using Stacked Deep Learning.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
PURPOSE: Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted i...

DI++: A deep learning system for patient condition identification in clinical notes.

Artificial intelligence in medicine
Accurately recording a patient's medical conditions in an EHR system is the basis of effectively documenting patient health status, coding for billing, and supporting data-driven clinical decision making. However, patient conditions are often not ful...

Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.

STAR protocols
MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a mach...

AI Integration in the Clinical Workflow.

Journal of digital imaging
Machine learning and artificial intelligence (AI) algorithms hold significant promise for addressing important clinical needs when applied to medical imaging; however, integration of algorithms into a radiology department is challenging. Vended algor...

An artificial intelligence platform to optimize workflow during ovarian stimulation and IVF: process improvement and outcome-based predictions.

Reproductive biomedicine online
RESEARCH QUESTION: Can workflow during IVF be facilitated by artificial intelligence to limit monitoring during ovarian stimulation to a single day and enable level-loading of retrievals?

Workflow for automatic renal perfusion quantification using ASL-MRI and machine learning.

Magnetic resonance in medicine
PURPOSE: Clinical applicability of renal arterial spin labeling (ASL) MRI is hampered because of time consuming and observer dependent post-processing, including manual segmentation of the cortex to obtain cortical renal blood flow (RBF). Machine lea...