Comments on: I, Medicine: Predictive Biometrics and Health Optimization

By: How To Measure Small Effects in Your Data | Quantified Self

How To Measure Small Effects in Your Data | Quantified Self — Fri, 26 Nov 2010 16:59:31 +0000

[...] was the question Bard Canning sent in for the QS Scientific Advisory Board. His challenge was met by Neil Rubens, Teresa Lunt and [...]

By: Alexandra Carmichael

Alexandra Carmichael — Tue, 02 Mar 2010 14:37:31 +0000

Thanks David and Bard for your comments! On the other side of the “collecting quality data” question, author and professor Clay Shirky is known to say that “the answer to bad data is more data,” so with enough data + powerful enough algorithms, it doesn’t really matter that much if it’s all standardized or not. I agree that the medical establishment will take a long time to accept this kind of data, but I don’t think their acceptance is necessarily required to start having an impact on helping people.

By: Bard

Bard — Tue, 02 Mar 2010 12:31:09 +0000

David, you are absolutely right. You’ve highlighted the number one issue that is likely to face this sector in the years to come – standardization.
I admire the courage and determination of people like Alexander Carmichael and Jamie Heywood who speak regularly about the significant correlations that their websites have identified – and how they have often been confirmed by subsequent medical studies.
Ultimately I’m not sure that it’s even necessary that the medical community accepts these technologies. All that matters is that the patients accept them and use them in their lives.
The proof is in the pudding, and if these systems can deliver even 10% of the results we are claiming they will, their success will be assured.

By: David Collin

David Collin — Tue, 08 Dec 2009 21:17:10 +0000

Great post. I fully agree that we’re headed to great increases in personal health monitoring. But it seems to me to have much impact a lot is going to have to be done to make sure data collected is credible. We’ll need standard measures and calibration. We’ll need open data standards. We’ll need standard protocols for data collection and handling. It seems to me it’s going to be hard to get acceptance of personal data by the medical establishment unless unless there’s some rigor in the collection process. And the work of heading toward this bigger goal needs to start soon before the marketing process turns all this into a hodgepodge of proprietary systems and services.