AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Workflow

Showing 351 to 360 of 539 articles

Clear Filters

Active learning using deep Bayesian networks for surgical workflow analysis.

International journal of computer assisted radiology and surgery
PURPOSE: For many applications in the field of computer-assisted surgery, such as providing the position of a tumor, specifying the most probable tool required next by the surgeon or determining the remaining duration of surgery, methods for surgical...

Enabling artificial intelligence in high acuity medical environments.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Acute patient treatment can heavily profit from AI-based assistive and decision support systems, in terms of improved patient outcome as well as increased efficiency. Yet, only very few applications have been reported because of the limited accessibi...

A Transition Control Mechanism for Artificial Bee Colony (ABC) Algorithm.

Computational intelligence and neuroscience
Artificial Bee Colony (ABC) algorithm inspired by the complex search and foraging behaviors of real honey bees is one of the most promising implementations of the Swarm Intelligence- (SI-) based optimization algorithms. Due to its robust and phase-di...

netDx: interpretable patient classification using integrated patient similarity networks.

Molecular systems biology
Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis, and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse da...

Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis.

Trends in cancer
Deep learning refers to a set of computer models that have recently been used to make unprecedented progress in the way computers extract information from images. These algorithms have been applied to tasks in numerous medical specialties, most exten...

Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.

Surgical endoscopy
INTRODUCTION: The most common way of assessing surgical performance is by expert raters to view a surgical task and rate a trainee's performance. However, there is huge potential for automated skill assessment and workflow analysis using modern techn...

Defining host-pathogen interactions employing an artificial intelligence workflow.

eLife
UNLABELLED: For image-based infection biology, accurate unbiased quantification of host-pathogen interactions is essential, yet often performed manually or using limited enumeration employing simple image analysis algorithms based on image segmentati...

Automated analysis of cardiovascular magnetic resonance myocardial native T mapping images using fully convolutional neural networks.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) myocardial native T mapping allows assessment of interstitial diffuse fibrosis. In this technique, the global and regional T are measured manually by drawing region of interest in motion-corrected T...

CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research.

BMC bioinformatics
BACKGROUND: Current multi-petaflop supercomputers are powerful systems, but present challenges when faced with problems requiring large machine learning workflows. Complex algorithms running at system scale, often with different patterns that require...