Machine Learning Applications in Healthcare - Transforming Healthcare, Episode 8, Part 2

Machine learning in healthcare allows prediction of a future where data, analysis and innovation work together to help patients without them realizing it.

One of the biggest uses of machine learning in healthcare is the identification and diagnosis of diseases which are otherwise considered hard to diagnose.

Machine learning can identify and diagnose cancers which are tough to catch during the initial stages.

Machine learning can identify and diagnose genetic diseases.

IBM Watson Genomics integrates cognitive computing with genome-based tumor sequencing to help make fast diagnosis.

Computer Vision technology uses both machine learning and deep learning.

Microsoft's InnerEye initiative uses Computer Vision for image diagnostic tools and image analysis.

A primary clinical application of machine learning lies in the early stage drug discovery process.

Microsoft's Project Hanover uses machine learning based technologies for developing AI based technology for cancer treatment.

Microsoft's Project Hanover uses machine learning for personalizing drug combinations for acute myeloid leukemia (AML).

Personalized treatments are more effective by pairing individual health with predictive analytics.

Personalized treatments are helpful for further research and better disease assessment.

IBM Watson Oncology leverages patient medical history to help generate multiple treatment options.