mmat's Profile
mmat
Submitted
Activity Feed
This was an interesting read about one the many potential applications of machine learning in healthcare. Your article touched on a couple of key challenges that I would like to press on further as I believe they meaningfully stall the potential application of the above tool.
As Sam noted above, the Framingham risk score is part of clinical practice today. In medicine, it typically takes about 8-10 years for clinical guidance published in literature (e.g., academic journals) to be widely adopted by physicians in their practice. This would make it very hard for the above program to gain traction and lead to behaviour change in the short term. This is further exacerbated, by two other factors you discussed: reimbursements, and tools needed to implement the program.
On reimbursements: While Partner’s has been moving meaningfully to risk-based contracts, MA is on the forefront of these types of contracts nation-wide. Large swathes of the country do not have the incentive structures in place for this program of early detection and monitoring to be financially viable.
On tools: Partner’s is one of the largest academic medical centers in the country, with many resources at its disposal. Its EHR has been customized to contain more data than typical home-grown or smaller scale EHRs at hospitals with fewer resources. I worry about the potential applicability of these programs to community-based hospitals throughout most of the country. Would they ever be able to implement this?
Loved this article as well as the Square’s move to provide loans to the small and mid-size businesses. To your question on data privacy, I wonder if, when Square sells the loan, they are not actually passing along the downstream data, but rather just the loan itself? This feels to me far more likely than the concern you pose of Square’s potential to transmit data without the lender’s consent (which I agree would be a significant ethical consideration!).
Really interesting read about how machine learning drive’s Airbnb’s growth and development. As I think about Airbnb’s goal to “own” the travel experience end to end, I do believe that machine learning can help them do this. However, for machine learning to be truly effective, Airbnb needs to own more data on the customer, upstream of the accommodation booking process and closer to trip ideation. Today hotel companies and airlines partner and share data back and forth to understand when customers are searching for or considering a trip in one destination. This allows the partner organization to launch targeted ads to capture that customer’s visit. Airbnb could consider similar partnerships to gain access to this data.
Really interesting read about the use of 3D printing at Chanel. In the very short term I see the benefit of 3D printing for manufacturing cost reduction. To date, this initiative feels largely like a big PR spend for Chanel (largely because we have such little visibility into the ROI of this investment). I’m interested to see where Chanel takes its 3D printers in the future.
Great read about Tesla’s open innovation policy! I agree with some of the commenters above that Tesla is likely quite “closed” when it comes to their most important IC (e.g., batteries) and also maintains a significant competitive advantage in terms of factory production capabilities. ksimmons raises an interesting distinction between the utility of open-source for hardware vs software companies. I agree that open source makes much more sense for software companies. As I think about the future of vehicles, I could see this moving to a more software driven business (e.g., self-driving vehicles). Tesla’s current policy may be helping to orient it for this software based future.
Great read! I agree with Farrah’s point about this being more of a marketing campaign than a true search for a new flavour to add to the SKUs on a permanent basis. As I view these innovation competitions and product lunches, I see them as a way for snack and beverage companies that have relatively constant purchasing (i.e., non-seasonal) to create limited time hype and drive a spike in sales coupled with renewed engagement with the brand. Frito-Lay seems to be on to something, as other brands are following suit. More recently, Polar Seltzer has created competitions for limited edition flavours and released seasonal seltzer flavours.