AIMC Topic: Machine Learning

Clear Filters Showing 31311 to 31320 of 34417 articles

Utilizing human intelligence in artificial intelligence for detecting glaucomatous fundus images using human-in-the-loop machine learning.

Indian journal of ophthalmology
PURPOSE: For diagnosing glaucomatous damage, we have employed a novel convolutional neural network (CNN) from TrueColor confocal fundus images to conquer the black box dilemma in artificial intelligence (AI). This neural network with CNN architecture...

Machine Learning Refinement of the NSQIP Risk Calculator: Who Survives the "Hail Mary" Case?

Journal of the American College of Surgeons
BACKGROUND: The American College of Surgeons (ACS) NSQIP risk calculator helps guide operative decision making. In patients with significant surgical risk, it may be unclear whether to proceed with "Hail Mary"-type interventions. To refine prediction...

Deep Convolutional Neural Networks Implementation for the Analysis of Urine Culture.

Clinical chemistry
BACKGROUND: Urine culture images collected using bacteriology automation are currently interpreted by technologists during routine standard-of-care workflows. Machine learning may be able to improve the harmonization of and assist with these interpre...

AutoSolvate: A toolkit for automating quantum chemistry design and discovery of solvated molecules.

The Journal of chemical physics
The availability of large, high-quality datasets is crucial for artificial intelligence design and discovery in chemistry. Despite the essential roles of solvents in chemistry, the rapid computational dataset generation of solution-phase molecular pr...

BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: The identification of compound-protein interactions (CPIs) is an essential step in the process of drug discovery. The experimental determination of CPIs is known for a large amount of funds and time it consumes. Computational model has th...

massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation.

Bioinformatics (Oxford, England)
MOTIVATION: Mass spectrometry imaging (MSI) provides rich biochemical information in a label-free manner and therefore holds promise to substantially impact current practice in disease diagnosis. However, the complex nature of MSI data poses computat...

Considerations for the implementation of machine learning into acute care settings.

British medical bulletin
INTRODUCTION: Management of patients in the acute care setting requires accurate diagnosis and rapid initiation of validated treatments; therefore, this setting is likely to be an environment in which cognitive augmentation of the clinician's provisi...

Knowledge distillation circumvents nonlinearity for optical convolutional neural networks.

Applied optics
In recent years, convolutional neural networks (CNNs) have enabled ubiquitous image processing applications. As such, CNNs require fast forward propagation runtime to process high-resolution visual streams in real time. This is still a challenging ta...