Objective

Cytopathology AI facilitates the analysis of liquid biopsies by offering clinical decision support to the clinician specialist, and workflow enhancements for the cytopathology laboratory staff. It leverages digital and computational cytology with the use of artificial intelligence based on image processing, deep learning and machine learning.

Outcome

Users can examine the measurements of patients available in a pre-loaded dataset (or) upload a new dataset, examine the predictions for a patient, understand the factors contributing to the predictions.

●      Faster screening

●      Improved accuracy

●      Increased reliability

Business Value

One can apply specialized algorithms to enhance the work of the pathologist and brings in cost efficiencies.

H2O's AI and Data Approaches

This solution is powered by the H2O AI Cloud Driverless AI AutoML, H2O-3, and H2O.ai Wave. The data science approaches include genetic algorithm, advanced feature engineering, classification algorithms, GLM, GBM, XGBoost, ensemble stacking, unsupervised similarity search algorithms and various machine learning interpretability algorithms