AIMC Topic: Algorithms

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Artificial intelligence and machine learning in ophthalmology: A review.

Indian journal of ophthalmology
Since the introduction of artificial intelligence (AI) in 1956 by John McCarthy, the field has propelled medicine, optimized efficiency, and led to technological breakthroughs in clinical care. As an important frontier in healthcare, AI has implicati...

Coded aperture compressive temporal imaging using complementary codes and untrained neural networks for high-quality reconstruction.

Optics letters
The coded aperture compressive temporal imaging (CACTI) modality is capable of capturing dynamic scenes with only a single-shot of a 2D detector. In this Letter, we present a specifically designed CACTI system to boost the reconstruction quality. Our...

VdistCox: Vertically distributed Cox proportional hazards model with hyperparameter optimization.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Vertically partitioned data is distributed data in which information about a patient is distributed across multiple sites. In this study, we propose a novel algorithm (referred to as VdistCox) for the Cox proportional hazards model (Cox model), which...

Contrastive learning of protein representations with graph neural networks for structural and functional annotations.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Although protein sequence data is growing at an ever-increasing rate, the protein universe is still sparsely annotated with functional and structural annotations. Computational approaches have become efficient solutions to infer annotations for unlab...

A Primer on Deep Learning-Based Cellular Image Classification of Changes in the Spatial Distribution of the Golgi Apparatus After Experimental Manipulation.

Methods in molecular biology (Clifton, N.J.)
The visual classification of cell images according to differences in the spatial patterns of subcellular structure is an important methodology in cell and developmental biology. Experimental perturbation of cell function can induce changes in the spa...

DockNet: high-throughput protein-protein interface contact prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Over 300 000 protein-protein interaction (PPI) pairs have been identified in the human proteome and targeting these is fast becoming the next frontier in drug design. Predicting PPI sites, however, is a challenging task that traditionally...

Assessment of artificial intelligence-aided reading in the detection of nasal bone fractures.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Artificial intelligence (AI) technology is a promising diagnostic adjunct in fracture detection. However, few studies describe the improvement of clinicians' diagnostic accuracy for nasal bone fractures with the aid of AI technology.

Relevance of Machine Learning to Predict the Inhibitory Activity of Small Thiazole Chemicals on Estrogen Receptor.

Current computer-aided drug design
BACKGROUND: Drug discovery requires the use of hybrid technologies for the discovery of new chemical substances. One of those interesting strategies is QSAR via applying an artificial intelligence system that effectively predicts how chemical alterat...

Differential Expression, Functional and Machine Learning Analysis of High-Throughput -Omics Data Using Open-Source Tools.

Methods in molecular biology (Clifton, N.J.)
Today, -omics analyses, including the systematic cataloging of messenger RNA and microRNA sequences or DNA methylation patterns in a cell population, organ or tissue sample, allow for an unbiased, comprehensive genome-level analysis of complex diseas...