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Workflow

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A Layered, Hybrid Machine Learning Analytic Workflow for Mouse Risk Assessment Behavior.

eNeuro
Accurate and efficient quantification of animal behavior facilitates the understanding of the brain. An emerging approach within machine learning (ML) field is to combine multiple ML-based algorithms to quantify animal behavior. These so-called hybri...

A Deep Learning Workflow for Mass-Forming Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma Classification Based on MRI.

Current oncology (Toronto, Ont.)
OBJECTIVE: Precise classification of mass-forming intrahepatic cholangiocarcinoma (MF-ICC) and hepatocellular carcinoma (HCC) based on magnetic resonance imaging (MRI) is crucial for personalized treatment strategy. The purpose of the present study w...

Developing an integrated approach based on geographic object-based image analysis and convolutional neural network for volcanic and glacial landforms mapping.

Scientific reports
Rapid detection and mapping of landforms are crucially important to improve our understanding of past and presently active processes across the earth, especially, in complex and dynamic volcanoes. Traditional landform modeling approaches are labor-in...

Prospective risk analysis of the online-adaptive artificial intelligence-driven workflow using the Ethos treatment system.

Zeitschrift fur medizinische Physik
PURPOSE: The recently introduced Varian Ethos system allows adjusting radiotherapy treatment plans to anatomical changes on a daily basis. The system uses artificial intelligence to speed up the process of creating adapted plans, comes with its own s...

BASIN: A Semi-automatic Workflow, with Machine Learning Segmentation, for Objective Statistical Analysis of Biomedical and Biofilm Image Datasets.

Journal of molecular biology
Micrograph comparison remains useful in bioscience. This technology provides researchers with a quick snapshot of experimental conditions. But sometimes a two- condition comparison relies on researchers' eyes to draw conclusions. Our Bioimage Analysi...

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation.

PloS one
In biotechnology, cell growth is one of the most important properties for the characterization and optimization of microbial cultures. Novel live-cell imaging methods are leading to an ever better understanding of cell cultures and their development....

Protocol to explain graph neural network predictions using an edge-centric Shapley value-based approach.

STAR protocols
Here we present EdgeSHAPer, a workflow for explaining graph neural networks by approximating Shapley values using Monte Carlo sampling. In this protocol, we describe steps to execute Python scripts for a chemical dataset from the original publication...

[Automation and the use of robots in the pathology laboratory : A journey through time and a consideration of efficiency].

Pathologie (Heidelberg, Germany)
In the past 20 years, numerous technical innovations were introduced to the histopathology laboratory, providing tools for improved standardization and occupational safety. Digital tracking serves as a backbone accompanying the workflow from the labe...

Artificial intelligence workflow quantifying muscle features on Hematoxylin-Eosin stained sections reveals dystrophic phenotype amelioration upon treatment.

Scientific reports
Cell segmentation is a key step for a wide variety of biological investigations, especially in the context of muscle science. Currently, automated methods still struggle to perform skeletal muscle fiber quantification on Hematoxylin-Eosin (HE) staine...

Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records.

Scientific reports
Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challengi...