AIMC Topic: Animals

Clear Filters Showing 7621 to 7630 of 8866 articles

Deep learning-based cell-specific gene regulatory networks inferred from single-cell multiome data.

Nucleic acids research
Gene regulatory networks (GRNs) provide a global representation of how genetic/genomic information is transferred in living systems and are a key component in understanding genome regulation. Single-cell multiome data provide unprecedented opportunit...

Toward a Free-Response Paradigm of Decision Making in Spiking Neural Networks.

Neural computation
Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspired computing systems due to their energy efficiency and similarities to biological information processing. In contrast to continuous-valued artificia...

Improving Recall in Sparse Associative Memories That Use Neurogenesis.

Neural computation
The creation of future low-power neuromorphic solutions requires specialist spiking neural network (SNN) algorithms that are optimized for neuromorphic settings. One such algorithmic challenge is the ability to recall learned patterns from their nois...

Replay as a Basis for Backpropagation Through Time in the Brain.

Neural computation
How episodic memories are formed in the brain is a continuing puzzle for the neuroscience community. The brain areas that are critical for episodic learning (e.g., the hippocampus) are characterized by recurrent connectivity and generate frequent off...

[Evaluation of the performance of the artificial intelligence - enabled snail identification system for recognition of and ].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
OBJECTIVE: To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of and in schistosomiasis-endemic areas of Yunnan Province.

RetOCTNet: Deep Learning-Based Segmentation of OCT Images Following Retinal Ganglion Cell Injury.

Translational vision science & technology
PURPOSE: We present RetOCTNet, a deep learning tool to segment the retinal nerve fiber layer (RNFL) and total retinal thickness automatically from optical coherence tomography (OCT) scans in rats following retinal ganglion cell (RGC) injury.

Identification and Validation of Biomarkers in Metabolic Dysfunction-Associated Steatohepatitis Using Machine Learning and Bioinformatics.

Molecular genetics & genomic medicine
BACKGROUND: The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is increasing annually. MASH can progress to cirrhosis and hepatocellular carcinoma. However, the early diagnosis of MASH is challenging.

Towards the Next Generation of Data-Driven Therapeutics Using Spatially Resolved Single-Cell Technologies and Generative AI.

European journal of immunology
Recent advances in multi-omics and spatially resolved single-cell technologies have revolutionised our ability to profile millions of cellular states, offering unprecedented opportunities to understand the complex molecular landscapes of human tissue...

Digital Twinning of Interorgan Communications.

Comprehensive Physiology
Recent advances in our ability to collect and process information, particularly through artificial intelligence, opens up some exciting possibilities for understanding interorgan communication and treating conditions that arise from that communicatio...

Instar identification and weight prediction of (Guenée) larvae using machine learning.

Bulletin of entomological research
The Asian corn borer, (Guenée), emerges as a significant threat to maize cultivation, inflicting substantial damage upon the crops. Particularly, its larval stage represents a critical point characterised by significant economic consequences on maiz...