Gene Mutation AI
Snowflake and H2O.ai Partner in Health
The genetic makeup of a patient is increasing in the consideration of medical diagnoses and drug discovery efforts. From the multiple types and subtypes of cancer to heart disease, to obesity or the immune response, An individual’s genetic predisposition plays an important role in a variety of diseases such as cancer, heart disease and obesity. It also plays a key role in examining immune response. A patient’s genetic information often determines the appropriate pharmaceutical intervention for a given diagnosis.
How It Works
H2O Gene Mutation AI combines the Snowflake database and the H2O AI Cloud to bring intelligent clinical decision support directly to clinicians and provide advanced analytics for pharmacogenomics and pharmacovigilance pipelines.
State-of-the-art Clinical Decision Support
Make AI part of the triage process, leveraging ML and patient data tables to evaluate disease risk.
Discover the Drivers for Individual Risk
Visualize and explore drivers automatically extracted from ML algorithms to estimate patient risk and store that output in table format.
Explore Avenues for Therapeutic Intervention
Understand how patient risk is affected by various factors, in a dose-response type what-if analysis, and store the results in tables.
Identification of Similar Patients
Look up tables of historical patients whose outcomes are known, find the most similar ones to the specific patient, and understand their similarities.
Evaluation of Demographic Biases
Use historical patient tables to evaluate any unintended biases in the model due to lack of demographic diversity in the patient population.
Integration of Multiple Data Types
Leverage a variety of data types, tables with different molecular results, clinical measurements, or medical notes for the same patients to further refine the disease model.
Genomic data is complex to handle at scale. Gene Mutation AI leverages H2O.ai models and Snowflake Data Cloud for speed and scalability, so that each of the technologies work cooperatively.
Easily understand genetically-driven, patient-specific drug efficacy and adverse effects.
With an easy-to-navigate interface that is easily accessible from a tablet or smartphone, physicians can examine a patient's genetic profile and gain insights on-demand.