AIMC Topic: Algorithms

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Histopathological Diagnosis System for Gastritis Using Deep Learning Algorithm.

Chinese medical sciences journal = Chung-kuo i hsueh k'o hsueh tsa chih
Objective To develope a deep learning algorithm for pathological classification of chronic gastritis and assess its performance using whole-slide images (WSIs). Methods We retrospectively collected 1,250 gastric biopsy specimens (1,128 gastritis, 122...

[Research on Self-perception and Active Warning Model of Medical Equipment Operation and Maintenance Status Based on Machine Learning Algorithm].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
The panoramic perception of medical equipment operation and maintenance status is the basic guarantee for the implementation of smart medical care, the machine learning algorithm-based autonomous perception and active early warning model of medical e...

CoCoNet: an efficient deep learning tool for viral metagenome binning.

Bioinformatics (Oxford, England)
MOTIVATION: Metagenomic approaches hold the potential to characterize microbial communities and unravel the intricate link between the microbiome and biological processes. Assembly is one of the most critical steps in metagenomics experiments. It con...

An enhanced loss function simplifies the deep learning model for characterizing the 3D organoid models.

Bioinformatics (Oxford, England)
MOTIVATION: Organization of the organoid models, imaged in 3D with a confocal microscope, is an essential morphometric index to assess responses to stress or therapeutic targets. In fact, differentiating malignant and normal cells is often difficult ...

Preventing dataset shift from breaking machine-learning biomarkers.

GigaScience
Machine learning brings the hope of finding new biomarkers extracted from cohorts with rich biomedical measurements. A good biomarker is one that gives reliable detection of the corresponding condition. However, biomarkers are often extracted from a ...

Neuromorphic learning with Mott insulator NiO.

Proceedings of the National Academy of Sciences of the United States of America
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence fou...

Towards Interpretable Machine Learning in EEG Analysis.

Studies in health technology and informatics
In this paper a machine learning model for automatic detection of abnormalities in electroencephalography (EEG) is dissected into parts, so that the influence of each part on the classification accuracy score can be examined. The most successful setu...

Machine learning algorithms to control concentrations of carbon nanocomplexes in a biological medium via optical absorption spectroscopy: how to choose and what to expect?

Applied optics
A solution of spectroscopic inverse problems, implying determination of target parameters of the research object via analysis of spectra of various origins, is an overly complex task, especially in case of strong variability of the research object. O...

Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: : Developing clinical natural language processing systems often requires access to many clinical documents, which are not widely available to the public due to privacy and security concerns. To address this challenge, we propose to develop...