Nature genetics has an editorial on the Mayo and Myriad cases. I agree with this bit: “In our opinion, it is not new judgments or legislation that are needed but more innovation. In the era of whole-genome sequencing of highly variable genomes, it is increasingly hard to justify exclusive ownership of particularly useful parts of the genome, and method claims must be more carefully described.” Via Andrew J. One of Tech Review’s 10 emerging technologies from a February 2003 article?
This is a great article about the illusion of progress in machine learning. In part, I think it explains why the Leekasso (just using the top 10) isn’t a totally silly idea. I also love how he talks about sources of uncertainty in real prediction problems that aren’t part of the classical models when developing prediction algorithms. I think that this is a hugely underrated component of building an accurate classifier - just finding the quirks particular to a type of data.
As Reeves alluded to in his post about the Mayo personalized medicine case, the Supreme Court just vacated the lower court’s ruling in Association for Molecular Pathology v. Myriad Genetics (No. 11-725). The case has been sent back down to the Federal Circuit for reconsideration in light of the Court’s decision in Mayo. This means that the Supreme Court thought the two cases were sufficiently similar that the lower courts should take another look using the new direction from Mayo.
The psychologist whose experiment didn’t replicate then went off on the scientists who did the replication experiment is at it again. I don’t see a clear argument about the facts of the matter in his post, just more name calling. This seems to be a case study in what not to do when your study doesn’t replicate. More on “conceptual replication” in there too. Berkeley is running a data science course with instructors Jeff Hammerbacher and Mike Franklin, I looked through the notes and it looks pretty amazing.
This is a guest post by Reeves Anderson, an associate at Arnold and Porter LLP. Reeves Anderson is a member of the Appellate and Supreme Court practice group at Arnold & Porter LLP in Washington, D.C. The views expressed herein are those of the author alone and not of Arnold & Porter LLP or any of the firm’s clients. Stay tuned for follow-up posts by the Simply Statistics crowd on the implications of this ruling for statistics in general and personalized medicine in particular.