13 Mar AI and Machine Learning in Healthcare – Not Just Hype Anymore

Eric Lefkofsky (CEO of Tempus and co-founder of Groupon):

“Treating a cancer patient without the benefit of modern software is the same as driving at night without headlights. If you don’t introduce some amount of data, you will end up going down the wrong path.”

AI and machine learning have received a lot of attention over the last year, poised to become a big game changer in many industries, including the healthcare sector. The industry is responding with a rise in potential applications with companies developing new approaches and innovative tools. The pharma sector is engaging AI to provide analytical solutions to accelerate drug development, while the tech industry is entering the healthcare market to build winning solutions, and the clinical sector is advancing AI for diagnostic decision making and treatment evaluation.

At the Precision Medicine World Conference PMWC 2018 Silicon Valley, Eric Lefkofsky (CEO of Tempus) was interviewed by Atul Butte (Director, Institute for Computational Health Sciences, UCSF). Eric shared his views on the biggest challenges in cancer treatment and how to best address them by finding value in the data. Find the full interview on the PMWC blog.

Eric: “We view this data challenge as a problem that can be solved. Meaning, we can put rich data into the hands of oncologists, pathologists, radiologists, surgeons, and researchers and we believe if you do that, you end up saving most probably 100,000 of the 600,000 patients a year from dying.”

The benefits of a data-driven healthcare are manifold and undeniable. Yet, for AI and machine learning to create the value needed, significant hurdles must be overcome. To arm the physician and researcher with the data they need, and to ensure patients will contribute to public data initiatives, orthogonal data sets (both clinical and molecular data) must be combined, proper bioinformatics and analytics tools must be in place, clinical data must be extracted from sometimes arcane medical record systems, and the data must be structured, cleansed, and understood. Clearly, a lot of work still needs to be done, but as Vinod Khosla commented at PMWC 2018 Silicon Valley:

“AI will do more for medicine in the next 20 years than all the biological sciences combined. AI is something that human beings can’t comprehend as it is exceeding the human capability, and as such it is challenging to fully understand the potential and how it will impact our lives, or healthcare in particular.”

PMWC 2018 Michigan, June 6-7, is a great opportunity for everybody in the field to learn, contribute, and help build a foothold for AI to become the reality in healthcare. We have invited (and continue to invite) a number of leading scientists and critical thought leaders who will review and cover relevant subjects in AI and deep/machine learning for two dedicated AI and machine learning sessions.

Here is the list of thought leaders that are among our confirmed presenters:

Eric Topol
The Scripps Research Institute (TSRI)

Francis Collins
National Institutes of Health (NIH)

Eric Lefkofsky
Tempus

Nancy Cox
Vanderbilt University

Jenna Wiens
University of Michigan

George Sledge
Stanford University

Susan A. Murphy
Harvard University

Julie Iskow
Medidata

In addition, we’ll have presentations from the following organizations:

• Ayasdi
• Athelas
• Children’s Mercy
• Ciitizen
• CosmosID
• Data4Cure
• Fred Hutchinson
• Genomenon
• Guardant Health
• Harvard
• IBM
• Immusoft
• iNDX Technology
• Karius
• LOOL Health
• Medical College of Wisconsin
• Medidata
• Mendel.ai
• Natera
• NorthShore University Health System
• One Medical
• Providence
• Scripps Research Institute
• Stanford
• Strata Oncology
• Tempus
• Theravance
• University of Michigan
• UCSF
• Vanderbilt University
• ViewCure
• Vertex
• Wayne State University

Looking forward to seeing many of you at the upcoming PMWC 2018 Michigan conference scheduled for June 6-7 in Ann Arbor, MI.