AIMC Topic: Pattern Recognition, Automated

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Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer.

The American journal of surgical pathology
Advances in the quality of whole-slide images have set the stage for the clinical use of digital images in anatomic pathology. Along with advances in computer image analysis, this raises the possibility for computer-assisted diagnostics in pathology ...

Machine learning for psychiatric patient triaging: an investigation of cascading classifiers.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Develop an approach, One-class-at-a-time, for triaging psychiatric patients using machine learning on textual patient records. Our approach aims to automate the triaging process and reduce expert effort while providing high classification ...

Learning Efficient Spatial-Temporal Gait Features with Deep Learning for Human Identification.

Neuroinformatics
The integration of the latest breakthroughs in bioinformatics technology from one side and artificial intelligence from another side, enables remarkable advances in the fields of intelligent security guard computational biology, healthcare, and so on...

Uyghur Text Matching in Graphic Images for Biomedical Semantic Analysis.

Neuroinformatics
How to read Uyghur text from biomedical graphic images is a challenge problem due to the complex layout and cursive writing of Uyghur. In this paper, we propose a system that extracts text from Uyghur biomedical images, and matches the text in a spec...

Texture analysis of magnetic resonance T1 mapping with dilated cardiomyopathy: A machine learning approach.

Medicine
The diagnosis of dilated cardiomyopathy (DCM) remains a challenge in clinical radiology. This study aimed to investigate whether texture analysis (TA) parameters on magnetic resonance T1 mapping can be helpful for the diagnosis of DCM.A total of 50 D...

Artificial intelligence in radiology.

Nature reviews. Cancer
Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in th...

Comparison of Shallow and Deep Learning Methods on Classifying the Regional Pattern of Diffuse Lung Disease.

Journal of digital imaging
This study aimed to compare shallow and deep learning of classifying the patterns of interstitial lung diseases (ILDs). Using high-resolution computed tomography images, two experienced radiologists marked 1200 regions of interest (ROIs), in which 60...

A Deep-Learning System for Fully-Automated Peripherally Inserted Central Catheter (PICC) Tip Detection.

Journal of digital imaging
A peripherally inserted central catheter (PICC) is a thin catheter that is inserted via arm veins and threaded near the heart, providing intravenous access. The final catheter tip position is always confirmed on a chest radiograph (CXR) immediately a...