AIMC Topic: Reference Standards

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ProteinNet: a standardized data set for machine learning of protein structure.

BMC bioinformatics
BACKGROUND: Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic machine learning problems like computer vision, progress has been driven by standardized ...

Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.

Medical physics
PURPOSE: Computed tomography (CT) is an effective method for detecting and characterizing lung nodules in vivo. With the growing use of chest CT, the detection frequency of lung nodules is increasing. Noninvasive methods to distinguish malignant from...

High-Sensitivity Determination of Nutrient Elements in by Laser-induced Breakdown Spectroscopy and Chemometric Methods.

Molecules (Basel, Switzerland)
High-accuracy and fast detection of nutritive elements in traditional Chinese medicine (PN) is beneficial for providing useful assessment of the healthy alimentation and pharmaceutical value of PN herbs. Laser-induced breakdown spectroscopy (LIBS) w...

Leveraging Electronic Dental Record Data to Classify Patients Based on Their Smoking Intensity.

Methods of information in medicine
BACKGROUND: Smoking is an established risk factor for oral diseases and, therefore, dental clinicians routinely assess and record their patients' detailed smoking status. Researchers have successfully extracted smoking history from electronic health ...

Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning.

Nature biomedical engineering
The histological analysis of tissue samples, widely used for disease diagnosis, involves lengthy and laborious tissue preparation. Here, we show that a convolutional neural network trained using a generative adversarial-network model can transform wi...

Streamlining Quality Review of Mass Spectrometry Data in the Clinical Laboratory by Use of Machine Learning.

Archives of pathology & laboratory medicine
CONTEXT.—: Turnaround time and productivity of clinical mass spectrometric (MS) testing are hampered by time-consuming manual review of the analytical quality of MS data before release of patient results.

Qualitative versus quantitative lumbar spinal stenosis grading by machine learning supported texture analysis-Experience from the LSOS study cohort.

European journal of radiology
PURPOSE: To investigate and compare the reproducibility and accuracy of qualitative ratings and quantitative texture analysis (TA) in detection and grading of lumbar spinal stenosis (LSS) in magnetic resonance imaging (MR) scans of the lumbar spine.

The practical implementation of artificial intelligence technologies in medicine.

Nature medicine
The development of artificial intelligence (AI)-based technologies in medicine is advancing rapidly, but real-world clinical implementation has not yet become a reality. Here we review some of the key practical issues surrounding the implementation o...

Development of a sandwich ELISA for determining plasma prolactin concentration in domestic birds.

Domestic animal endocrinology
The present study was conducted to establish a sandwich ELISA for the determination of prolactin (PRL) concentrations in the plasma of domestic fowls. The assay uses a recombinant goose PRL as the reference standard, expressed in a eukaryotic system,...