AIMC Topic: Automation

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Towards near real-time assessment of surgical skills: A comparison of feature extraction techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Surgical skill assessment aims to objectively evaluate and provide constructive feedback for trainee surgeons. Conventional methods require direct observation with assessment from surgical experts which are both unscalable a...

Disease phenotype synonymous prediction through network representation learning from PubMed database.

Artificial intelligence in medicine
Synonym mapping between phenotype concepts from different terminologies is difficult because terminology databases have been developed largely independently. Existing maps of synonymous phenotype concepts from different terminology databases are high...

Exploiting open source 3D printer architecture for laboratory robotics to automate high-throughput time-lapse imaging for analytical microbiology.

PloS one
Growth in open-source hardware designs combined with the low-cost of high performance optoelectronic and robotics components has supported a resurgence of in-house custom lab equipment development. We describe a low cost (below $700), open-source, fu...

Deep learning algorithms for automated detection of Crohn's disease ulcers by video capsule endoscopy.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The aim of our study was to develop and evaluate a deep learning algorithm for the automated detection of small-bowel ulcers in Crohn's disease (CD) on capsule endoscopy (CE) images of individual patients.

The digital surgeon: How big data, automation, and artificial intelligence will change surgical practice.

Journal of pediatric surgery
Exponential growth in computing power, data storage, and sensing technology has led to a world in which we can both capture and analyze incredible amounts of data. The evolution of machine learning has further advanced the ability of computers to dev...

Application of a fully deep convolutional neural network to the automation of tooth segmentation on panoramic radiographs.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: To evaluate a fully deep learning mask region-based convolutional neural network (R-CNN) method for automated tooth segmentation using individual annotation of panoramic radiographs.

AOCT-NET: a convolutional network automated classification of multiclass retinal diseases using spectral-domain optical coherence tomography images.

Medical & biological engineering & computing
Since introducing optical coherence tomography (OCT) technology for 2D eye imaging, it has become one of the most important and widely used imaging modalities for the noninvasive assessment of retinal eye diseases. Age-related macular degeneration (A...

Automatic detection of arrhythmia from imbalanced ECG database using CNN model with SMOTE.

Australasian physical & engineering sciences in medicine
Timely prediction of cardiovascular diseases with the help of a computer-aided diagnosis system minimizes the mortality rate of cardiac disease patients. Cardiac arrhythmia detection is one of the most challenging tasks, because the variations of ele...

WormBot, an open-source robotics platform for survival and behavior analysis in C. elegans.

GeroScience
Caenorhabditis elegans is a popular organism for aging research owing to its highly conserved molecular pathways, short lifespan, small size, and extensive genetic and reverse genetic resources. Here we describe the WormBot, an open-source robotic im...

Automatic detection on intracranial aneurysm from digital subtraction angiography with cascade convolutional neural networks.

Biomedical engineering online
BACKGROUND: An intracranial aneurysm is a cerebrovascular disorder that can result in various diseases. Clinically, diagnosis of an intracranial aneurysm utilizes digital subtraction angiography (DSA) modality as gold standard. The existing automatic...