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USE CASE

Chest Abnormality Detection

Objective

Chest X-Rays (CXRs) are widely used for diagnosing abnormalities in the heart and lung area. Automatically detecting these abnormalities with high accuracy could greatly enhance real world diagnosis processes Chest abnormality detection solution is built with an objective to develop a decision support system for data scientists and clinician to detect abnormalities in chest x-ray.

Outcome

The solution is a computer vision prototype for the detection and identification of different types of anomalies from X-ray images, aimed at both data scientists and clinicians.

Business Value

The solution enables timely clinical intervention support, cost optimization and improved quality of patient care. Chest abnormality detector enables quicker diagnosis and cheaper with a reduced reliance on the intervention of human experts.

H2O's AI and Data Approaches

H2O Hydrogen Torch is an offering within the H2O Platform. It enables novice and master data scientists to solve use cases in the area of clinical computer vision and natural language problems.

 

Resources

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