AIMC Topic: Algorithms

Clear Filters Showing 26351 to 26360 of 28713 articles

Integrating landmark modeling framework and machine learning algorithms for dynamic prediction of tuberculosis treatment outcomes.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This study aims to establish an informative dynamic prediction model of treatment outcomes using follow-up records of tuberculosis (TB) patients, which can timely detect cases when the current treatment plan may not be effective.

TransformerGO: predicting protein-protein interactions by modelling the attention between sets of gene ontology terms.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interactions (PPIs) play a key role in diverse biological processes but only a small subset of the interactions has been experimentally identified. Additionally, high-throughput experimental techniques that detect PPIs are...

GMNN2CD: identification of circRNA-disease associations based on variational inference and graph Markov neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: With the analysis of the characteristic and function of circular RNAs (circRNAs), people have realized that they play a critical role in the diseases. Exploring the relationship between circRNAs and diseases is of far-reaching significanc...

Characterizing aircraft wake vortex position and strength using LiDAR measurements processed with artificial neural networks.

Optics express
The position and strength of wake vortices captured by LiDAR (Light Detection and Ranging) instruments are usually determined by conventional approaches such as the Radial Velocity (RV) method. Promising wake vortex detection results of LiDAR measure...

Deep learning-based ballistocardiography reconstruction algorithm on the optical fiber sensor.

Optics express
Ballistocardiography (BCG) is a vibration signal related to cardiac activity, which can be obtained in a non-invasive way by optical fiber sensors. In this paper, we propose a modified generative adversarial network (GAN) to reconstruct BCG signals b...

Artificial Intelligence in Oncology: Current Capabilities, Future Opportunities, and Ethical Considerations.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
The promise of highly personalized oncology care using artificial intelligence (AI) technologies has been forecasted since the emergence of the field. Cumulative advances across the science are bringing this promise to realization, including refineme...

RNN-based deep learning for physical activity recognition using smartwatch sensors: A case study of simple and complex activity recognition.

Mathematical biosciences and engineering : MBE
Currently, identification of complex human activities is experiencing exponential growth through the use of deep learning algorithms. Conventional strategies for recognizing human activity generally rely on handcrafted characteristics from heuristic ...

Machine Learning Applied to Routinely Collected Health Administrative Data.

Healthcare quarterly (Toronto, Ont.)
There has been considerable growth in the development of machine learning algorithms for clinical applications. The authors survey recent machine learning models developed with the use of large health administrative databases at ICES and highlight th...

Artificial Intelligence in Kidney Cancer.

American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Artificial intelligence is rapidly expanding into nearly all facets of life, particularly within the field of medicine. The diagnosis, characterization, management, and treatment of kidney cancer is ripe with areas for improvement that may be met wit...