AIMC Topic: Workflow

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CPEM: Accurate cancer type classification based on somatic alterations using an ensemble of a random forest and a deep neural network.

Scientific reports
With recent advances in DNA sequencing technologies, fast acquisition of large-scale genomic data has become commonplace. For cancer studies, in particular, there is an increasing need for the classification of cancer type based on somatic alteration...

Same-day antimicrobial susceptibility test using acoustic-enhanced flow cytometry visualized with supervised machine learning.

Journal of medical microbiology
Antimicrobial susceptibility is slow to determine, taking several days to fully impact treatment. This proof-of-concept study assessed the feasibility of using machine-learning techniques for analysis of data produced by the flow cytometer-assisted ...

Technical Note: Ontology-guided radiomics analysis workflow (O-RAW).

Medical physics
PURPOSE: Radiomics is the process to automate tumor feature extraction from medical images. This has shown potential for quantifying the tumor phenotype and predicting treatment response. The three major challenges of radiomics research and clinical ...

ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning.

Scientific reports
Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely a...

Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: The ECG remains the most widely used diagnostic test for characterization of cardiac structure and electrical activity. We hypothesized that parallel advances in computing power, machine learning algorithms, and availability of large-scal...

Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.

The Journal of pathology
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated pa...

Measurement-oriented deep-learning workflow for improved segmentation of myelin and axons in high-resolution images of human cerebral white matter.

Journal of neuroscience methods
BACKGROUND: Standard segmentation of high-contrast electron micrographs (EM) identifies myelin accurately but does not translate easily into measurements of individual axons and their myelin, even in cross-sections of parallel fibers. We describe aut...