Intel® AI for Healthcare

 
From creating new techniques for patient diagnosis to discovering cures, Intel has contributed to the application of AI in healthcare.

Leading the Progress of AI in Healthcare

The University of Southern California, San Francisco, uses BigDL for Apache Spark* to develop and train an AI model for early identification of osteoporosis and other clinical care challenges.

With this pioneering collaboration, Intel is leading efforts to bring AI and high-performance computing to research and clinical oncology. 

Using Intel® Xeon® Scalable processors, Lenovo* enterprise workstations process Diaceutics' vast database of patient test data. This enables providers to use AI-based techniques and gain real-time insight from diagnostic testing.

Survey reveals attitudes about AI and perceived barriers to adoption in this survey of 200 U.S. healthcare decision-makers.

Kyoto University Graduate School of Medicine is using Intel® AI Technology to aid in the discovery of new drugs and reduction of research and development costs.

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Lessons in Applying AI Algorithms to Healthcare

Map Brain Connectivity Using Artificial Intelligence

See how AI algorithms can help visualize brain connectivity more effectively in cases of neurological diseases.

Biomedical Image Segmentation Using U-Net

Learn to train a U-Net model to review MRI scans and accurately predict where tumors exist.

Predict Patient Costs with Machine Learning

This video from the Portland AI Meetup includes a talk about how machine learning can help predict patient costs for hospitals.

AI Powers Clinical Trials

Machine learning can assist clinicians to improve the quality and lower the cost of clinical trials for better patient care.

CPUs for Medical Image Analysis

Take advantage of the large memory capacity in CPUs to effectively support 3D convolutional neural networks (CNNs) for medical image analysis.

Hands-On with AI Projects