Data Analytics, Machine Learning and AI for the Healthcare Industry - Databricks


Data Analytics and Machine Learning for the Healthcare Industry

Harness the power of big data and AI to personalize healthcare and improve patient outcomes


Enabling Patient-centric Healthcare with Data Analytics and AI

Enable healthcare organizations to drive innovations in patient care while reducing costs with big data analytics, machine and AI — powered by the Databricks Unified Data Analytics Platform.


Build anomaly detection models on top of claims, billing, and behavioral data to identify and prevent payment of fraudulent claims, unnecessary treatments or potential identity theft.


Predictively determine best treatments and optimize the quality of care through the aggregation and analysis of relevant patient history and care data across all healthcare channels.


Leverage machine learning to drive operational efficiencies across a variety of areas such as preventing patient readmission, predicting bed utilization, transcribing doctors notes and more.


Improving Healthcare Outcomes with Data Science at Scale

Learn how the healthcare industry is applying the latest machine learning techniques against massive volumes of clinical data to drive innovations in care


Extracting Real-world Insights from Population-scale Clinical Data

Learn how Prognos built ML pipelines on 25 billion clinical lab records with Databricks, Apache Spark™ and AWS

Watch Now
Customer Video

Improving Care with Predictive Medicine at Sanford Health

Learn how Sanford Health is leveraging machine learning to provide customized treatments for patients. By making primary care recommendations on a patients health history and genetic background, Sanford personalizes preventative treatment instead of using a “one size fits all” approach.

Watch Now
Customer Talk

Be Patient: Building Advanced Analytics at Optum with Patients at the Heart

Optum is a leading health services company servicing more than 126 million patients. In this Spark + AI Summit talk, Optum shares how they use machine learning on Databricks and Spark to predict chronic disease from historical claims and clinical data.

Watch Now
Customer Case Study

Providing Digital Health Services to Better Address Patient Needs

HealthDirect Australia reduced the processing latency for a dataset with millions of healthcare records from a day to minutes. This improved latency provides them a real-time view of the patients they service, enabling them to provide more timely services to the citizens of Australia.

Read More

Predicting Sepsis and Solving Other Clinical Challenges with Unified Analytics

In this recorded webinar with Prominence Advisors, you will learn how to unlock insights buried in siloed EHR data. With the power of the scalable Databricks platform, you can build power predictive models that can help identify patients at a high-risk of developing sepsis.

Watch Now
Customer Talk

Data Governance Lessons Learned from Centers for Medicare and Medicaid Services

In this technical talk, NewWave shares an open-source data validation framework they built on Apache Spark for the Centers for Medicare and Medicaid Services.

Watch Now

Automated Monitoring of Medical Device Data with Machine Learning

Learn how to build an end-to-end ML pipeline for streaming EKG data using Delta Lake, Keras and MLflow.

Watch Now

Real-World Evidence Analytics at Scale

Learn how to accelerate drug development and improve healthcare delivery with a unified approach to analyzing population-scale real-world data.

Download Now
"Databricks allows us to take clinical research and development and turn it into a clinically validated screen in far less time, which allows us to save us a lot of the money and effort it would generally require to do this on our own on-premises computational platforms."

Read the Case Study

Lynn Carmichael, Senior Director of Computational Bioinformatics, Sanford Health

Ready to get started?

Try Databricks For Free