AIMC Topic: Algorithms

Clear Filters Showing 27281 to 27290 of 28713 articles

Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

JAMA ophthalmology
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...

Protein-ligand binding residue prediction enhancement through hybrid deep heterogeneous learning of sequence and structure data.

Bioinformatics (Oxford, England)
MOTIVATION: Knowledge of protein-ligand binding residues is important for understanding the functions of proteins and their interaction mechanisms. From experimentally solved protein structures, how to accurately identify its potential binding sites ...

PlasGUN: gene prediction in plasmid metagenomic short reads using deep learning.

Bioinformatics (Oxford, England)
SUMMARY: We present the first tool of gene prediction, PlasGUN, for plasmid metagenomic short-read data. The tool, developed based on deep learning algorithm of multiple input Convolutional Neural Network, demonstrates much better performance when te...

Beyond the Artificial Intelligence Hype: What Lies Behind the Algorithms and What We Can Achieve.

Journal of thoracic imaging
The field of artificial intelligence (AI) is currently experiencing a period of extensive growth in a wide variety of fields, medicine not being the exception. The base of AI is mathematics and computer science, and the current fame of AI in industry...

Polar labeling: silver standard algorithm for training disease classifiers.

Bioinformatics (Oxford, England)
MOTIVATION: Expert-labeled data are essential to train phenotyping algorithms for cohort identification. However expert labeling is time and labor intensive, and the costs remain prohibitive for scaling phenotyping to wider use-cases.

Incorporating natural language processing to improve classification of axial spondyloarthritis using electronic health records.

Rheumatology (Oxford, England)
OBJECTIVES: To develop classification algorithms that accurately identify axial SpA (axSpA) patients in electronic health records, and compare the performance of algorithms incorporating free-text data against approaches using only International Clas...

[Progress in biomedical data analysis based on deep learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Traditional biomedical data analysis technology faces enormous challenges in the context of the big data era. The application of deep learning technology in the field of biomedical analysis has ushered in tremendous development opportunities. In this...

[A fusion network model based on limited training samples for the automatic segmentation of pelvic endangered organs].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
When applying deep learning to the automatic segmentation of organs at risk in medical images, we combine two network models of Dense Net and V-Net to develop a Dense V-network for automatic segmentation of three-dimensional computed tomography (CT) ...

Retinal blood vessel segmentation based on Densely Connected U-Net.

Mathematical biosciences and engineering : MBE
The segmentation of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper proposes a new architecture of the U-Net network for retinal blood vessel segmentation. Adding dense block to U-N...

[Multi-feature Extraction and Classification of Breast Tumor in Ultrasound Image].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: Feature extraction of breast tumors is very important in the breast tumor detection (benign and malignant) in ultrasound image. The traditional quantitative description of breast tumors has some shortcomings, such as inaccuracy. A simple a...