AIMC Topic: Deep Learning

Clear Filters Showing 4511 to 4520 of 28423 articles

Deep Learning Architecture to Infer Kennedy Classification of Partially Edentulous Arches Using Object Detection Techniques and Piecewise Annotations.

International dental journal
OBJECTIVES: Dental health is integral to overall well-being, with early detection of issues critical for prevention. This research work focuses on utilizing artificial intelligence and deep learning-based object detection techniques for automated det...

Protein-protein interaction detection using deep learning: A survey, comparative analysis, and experimental evaluation.

Computers in biology and medicine
This survey paper provides a comprehensive analysis of various Deep Learning (DL) techniques and algorithms for detecting protein-protein interactions (PPIs). It examines the scalability, interpretability, accuracy, and efficiency of each technique, ...

Deep learning using histological images for gene mutation prediction in lung cancer: a multicentre retrospective study.

The Lancet. Oncology
BACKGROUND: Accurate detection of driver gene mutations is crucial for treatment planning and predicting prognosis for patients with lung cancer. Conventional genomic testing requires high-quality tissue samples and is time-consuming and resource-con...

A deep learning approach to predict differentiation outcomes in hypothalamic-pituitary organoids.

Communications biology
We use three-dimensional culture systems of human pluripotent stem cells for differentiation into pituitary organoids. Three-dimensional culture is inherently characterized by its ability to induce heterogeneous cell populations, making it difficult ...

[PSI]-CIC: A Deep-Learning Pipeline for the Annotation of Sectored Saccharomyces cerevisiae Colonies.

Bulletin of mathematical biology
The prion phenotype in yeast manifests as a white, pink, or red color pigment. Experimental manipulations destabilize prion phenotypes, and allow colonies to exhibit (red) sectored phenotypes within otherwise completely white colonies. Further inve...

Deep Learning for Contrast Enhanced Mammography - A Systematic Review.

Academic radiology
BACKGROUND/AIM: Contrast-enhanced mammography (CEM) is a relatively novel imaging technique that enables both anatomical and functional breast imaging, with improved diagnostic performance compared to standard 2D mammography. The aim of this study is...

Dongting Lake algal bloom forecasting: Robustness and accuracy analysis of deep learning models.

Journal of hazardous materials
Harmful algal blooms (HABs) pose a significant threat to aquatic ecosystems, prompting efforts to predict their occurrence for swift action by water management agencies. Despite the potential for high-precision forecasting through machine learning, t...

Explainable exercise recommendation with knowledge graph.

Neural networks : the official journal of the International Neural Network Society
Recommending suitable exercises and providing the reasons for these recommendations is a highly valuable task, as it can significantly improve students' learning efficiency. Nevertheless, the extensive range of exercise resources and the diverse lear...

M4Net: Multi-level multi-patch multi-receptive multi-dimensional attention network for infrared small target detection.

Neural networks : the official journal of the International Neural Network Society
The detection of infrared small targets is getting more and more attention, and has a wider application in both military and civilian fields. The traditional infrared small target detection methods heavily rely on the setting of manual features, and ...

An extrapolation-driven network architecture for physics-informed deep learning.

Neural networks : the official journal of the International Neural Network Society
Current physics-informed neural network (PINN) implementations with sequential learning strategies often experience some weaknesses, such as the failure to reproduce the previous training results when using a single network, the difficulty to strictl...